readme

Espressif DSP Library

ESP-DSP is the official DSP library for ESP32 and ESP32-S3 chips.

Overview

ESP-DSP is intended to be used as an ESP-IDF component. For the introduction to ESP-IDF, refer to the ESP-IDF Programming Guide.

The ESP-DSP library includes implementations of the following functions:

Matrix multiplication: reference
Dot product: reference, example
FFT: reference, example
IIR: reference, example
FIR: reference
Vector math operations: reference
Kalman filter: reference

Many of the library functions are written in assembly and are optimized for the CPU configuration used in the ESP32. In addition to the optimized implementations, reference implementations written in ANSI C are provided.

Function implementations are provided for single precision floating point (32-bit float), and 16-bit signed integers.

Documentation

Documentation found in the above links is automatically generated from the contents of this repository. If you find that some information is missing or incomplete, please report an issue.

Installation and Usage

The ESP-DSP library is a component for the ESP-IDF build system.

The recommended way to use the component is to install it from the IDF Component Registry.

Adding ESP-DSP component to an existing project

In the project directory, run:

idf.py add-dependency "espressif/esp-dsp"

This will add the esp-dsp component as a dependency to the main component of your project. You can also add it by editing the idf_component.yml file manually.

Downloading ESP-DSP examples

You can download the example projects from the IDF Component Registry website or use the idf.py create-project-from-example command. For example:

idf.py create-project-from-example "espressif/esp-dsp:basic_math"

Please refer to the IDF Component Registry for the download links and the instructions.

You can also use Git to clone this repository and find all the examples in the examples/ subdirectory. For the list of the examples, please see README.md in the examples directory.

Building and running ESP-DSP examples

Build, flash and monitor as this is usually done for ESP-IDF projects:

idf.py -p PORT flash monitor

where PORT is the UART port name of your development board, such as /dev/ttyUSB0 or COM1.

Note that you need to set up ESP-IDF before building the project. Refer to the ESP-IDF Getting Started Guide if you don't have the environment set up yet.

Reporting Issues

If you have found an issue in ESP-DSP, or wish to submit an enhancement request, please use the Issues section on Github.

For general questions related to this library, please use the esp32.com forum.

Contributing to ESP-DSP

Please check CONTRIBUTING.md if you'd like to contribute to ESP-DSP.

Copyrights and License

changelog

Esp-dsp Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.4.0] 2023-05-29

Added

Complex signal generator dsps_cplx_gen()
FIR f32 filter optimized for esp32s3
Memcpy and Memset optimized for esp32s3

Fixed

Fix in tests to pass
Minimum coeffcient length for fird_s16
Include malloc.h into dsps_fft4r_fc32_ansi.c
Fix for calculation length for dsps_corr_f32_axxx

Changed

Removed

[1.3.0] 2023-03-10

Added

Fixed point FIR filter with decimation
Update tag to 1.2.1 for component manager
Extend dsp_power_of_two() to 32-bit value

Fixed

add various links to idf_component.yml, exclude unnecessary files
cmake: update component CMakeLists.txt file syntax to IDF v4.x+
docs: move instructions for contributors into CONTRIBUTING.md
docs: update README.md to use IDF component manager for installation
drop IDF v4.0 and v4.1 support, add a CI build with IDF release/v5.0
examples: remove GNU Make instructions from README files
examples: allow examples to be installed from the component manager
Fix for fft_cplx2reC_f32 function
Wno-format-fix related errors
Wrong path for extra component directory

Changed

Removed

[1.2.0] 2022-09-22

readme of basic_math example

Basic Math Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use basic math functions from esp-dsp library. Example does the following steps:

Initialize the library
Initialize input signals with 1024 samples
Apply window to input signal by standard C loop.
Calculate FFT for 1024 complex samples and show the result
Show results on the plots
Apply window to input signal by basic math functions dsps_mul_f32 and dsps_mulc_f32.
Calculate FFT for 1024 complex samples
Show results on the plots

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (132) main: *** Start Example. ***
I (132) main: *** Multiply tone signal with Hann window by standard C loop. ***
I (152) view: Data min[432] = -173.749878, Data max[205] = 23.849705
 ________________________________________________________________
0                         |                                      |
1                         |                                      |
2                         |                                      |
3                         ||                                     |
4                        | |                                     |
5                       ||  |                                    |
6                    |||     ||                                  |
7               |||||          ||||                              |
8|||||||||||||||                   ||||||                        |
9                                        |||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (162) view: Plot: Length=512, min=-120.000000, max=40.000000
I (162) main: *** Multiply tone signal with Hann window by esp-dsp basic math functions. ***
I (162) view: Data min[432] = -173.749878, Data max[205] = 23.849705
 ________________________________________________________________
0                         |                                      |
1                         |                                      |
2                         |                                      |
3                         ||                                     |
4                        | |                                     |
5                       ||  |                                    |
6                    |||     ||                                  |
7               |||||          ||||                              |
8|||||||||||||||                   ||||||                        |
9                                        |||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (172) view: Plot: Length=512, min=-120.000000, max=40.000000
I (172) main: *** End Example. ***

readme of dotprod example

Dot Product Calculation Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use dotprod dsps_dotprod_f32 from esp-dsp library. Example does the following steps:

Initialize the input arrays
Calculate dot product of two arrays
Compare results and calculate execution time in cycles.

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (55) main: Start Example.
I (55) main: The sum of 101 elements from 0..100 = 5050.000000
I (55) main: Operation for 101 samples took 1381 cycles
I (65) main: End Example.

readme of fft example

FFT Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use FFT functionality from esp-dsp library. Example does the following steps:

Initialize the library
Initialize input signals with 1024 samples: one 0 dB, second with -20 dB
Combine two signals as one complex input signal and apply window to input signals paar.
Calculate FFT for 1024 complex samples
Apply bit reverse operation for output complex vector
Split one complex FFT output spectrum to two real signal spectrums
Show results on the plots
Show execution time of FFT

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (59) main: Start Example.
W (89) main: Signal x1
I (89) view: Data min[495] = -162.760925, Data max[164] = 23.938747
 ________________________________________________________________
0                                                                |
1                    |                                           |
2                    |                                           |
3                    |                                           |
4                    |                                           |
5                    |                                           |
6                   | |                                          |
7                   | |                                          |
8                  || ||                                         |
9||||||||||||||||||     ||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (159) view: Plot: Length=512, min=-60.000000, max=40.000000
W (169) main: Signal x2
I (169) view: Data min[502] = -164.545135, Data max[205] = 3.857752
 ________________________________________________________________
0                                                                |
1                                                                |
2                                                                |
3                         |                                      |
4                         |                                      |
5                         |                                      |
6                         |                                      |
7                         ||                                     |
8                        | |                                     |
9||||||||||||||||||||||||   ||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (249) view: Plot: Length=512, min=-60.000000, max=40.000000
W (249) main: Signals x1 and x2 on one plot
I (259) view: Data min[505] = -159.215271, Data max[164] = 23.938747
 ________________________________________________________________
0                                                                |
1                    |                                           |
2                    |                                           |
3                    |    |                                      |
4                    |    |                                      |
5                    |    |                                      |
6                   | |   |                                      |
7                   | |   ||                                     |
8                  || || | |                                     |
9||||||||||||||||||     |   ||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (339) view: Plot: Length=512, min=-60.000000, max=40.000000
I (339) main: FFT for 1024 complex points take 140472 cycles
I (349) main: End Example.

readme of fft4real example

FFT 4 Real Input Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use FFT functionality from esp-dsp library. Example does the following steps:

Initialize the library
Initialize input signals with 1024 samples: one 0 dB, second with -20 dB
Calculate FFT Radix-2 for 1024 complex samples
Calculate FFT Radix-4 for 1024 complex samples
Apply bit reverse operation for output complex vectors
Show results on the plots
Show execution time of FFTs

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (344) main: Start Example.
W (424) main: Signal x1
I (424) view: Data min[673] = -103.113297, Data max[328] = 20.490950
 ________________________________________________________________
0                                                                |
1                    |                                           |
2                    |                                           |
3                    |                                           |
4                    |                                           |
5                    |                                           |
6                    |                                           |
7                   | |                                          |
8                   | |                                          |
9|||||||||||||||||||   |||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (494) view: Plot: Length=1024, min=-60.000000, max=40.000000
W (504) main: Signal x2
I (504) view: Data min[582] = -103.113297, Data max[328] = 20.490950
 ________________________________________________________________
0                                                                |
1                    |                                           |
2                    |                                           |
3                    |                                           |
4                    |                                           |
5                    |                                           |
6                    |                                           |
7                   | |                                          |
8                   | |                                          |
9|||||||||||||||||||   |||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (584) view: Plot: Length=1024, min=-60.000000, max=40.000000
W (593) main: Difference between signals x1 and x2 on one plot
I (594) view: Data min[0] = 0.000000, Data max[392] = 0.313019
 ________________________________________________________________
0                                                                |
1                                                                |
2                                                                |
3                                                                |
4                                                                |
5                                                                |
6                                                                |
7                                                                |
8----------------------------------------------------------------|
9                                                                |
 0123456789012345678901234567890123456789012345678901234567890123
I (674) view: Plot: Length=1024, min=0.000000, max=40.000000
I (674) main: FFT Radix 2 for 1024 complex points take 168652 cycles
I (684) main: FFT Radix 4 for 1024 complex points take 104665 cycles
I (694) main: End Example.

readme of fft_window example

FFT Window Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use Window and FFT functionality from esp-dsp library. Example does the following steps:

Initialize the library
Initialize input signals with 1024 samples
Apply window to input signal.
Calculate FFT for 1024 complex samples
Apply bit reverse operation for output complex vector
Split one complex FFT output spectrum to two real signal spectrums
Show results on the plots

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (128) main: Start Example.
W (128) main: Hann Window
I (128) view: Data min[256] = -inf, Data max[1] = 24.086628
 ________________________________________________________________
0|                                                               |
1|                                                               |
2|                                                               |
3|                                                               |
4|                                                               |
5 |                                                              |
6  |                                                             |
7   |||||                                                        |
8        |||||||||||||||                                         |
9                       ||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (138) view: Plot: Length=512, min=-120.000000, max=40.000000
W (138) main: Blackman Window
I (148) view: Data min[355] = -165.295654, Data max[1] = 24.083012
 ________________________________________________________________
0|                                                               |
1|                                                               |
2|                                                               |
3|                                                               |
4|                                                               |
5|                                                               |
6 |                                                              |
7  |||                                                           |
8     |||||||||                                                  |
9              |||||||||||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (158) view: Plot: Length=512, min=-120.000000, max=40.000000
W (158) main: Blackman-Harris Window
I (168) view: Data min[128] = -inf, Data max[1] = 23.874702
 ________________________________________________________________
0|                                                               |
1|                                                               |
2|                                                               |
3|                                                               |
4|                                                               |
5|                                                               |
6|                                                               |
7||                                                              |
8| ||||                                                          |
9      |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (178) view: Plot: Length=512, min=-120.000000, max=40.000000
W (178) main: Blackman-Nuttall Window
I (188) view: Data min[128] = -inf, Data max[1] = 23.890663
 ________________________________________________________________
0|                                                               |
1|                                                               |
2|                                                               |
3|                                                               |
4|                                                               |
5|                                                               |
6|                                                               |
7 ||                                                             |
8   |||| |                                                       |
9       | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (198) view: Plot: Length=512, min=-120.000000, max=40.000000
W (198) main: Nuttall Window
I (208) view: Data min[203] = -175.147400, Data max[1] = 23.858671
 ________________________________________________________________
0|                                                               |
1|                                                               |
2|                                                               |
3|                                                               |
4|                                                               |
5|                                                               |
6|                                                               |
7||                                                              |
8  |||                                                           |
9     ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (218) view: Plot: Length=512, min=-120.000000, max=40.000000
W (218) main: Flat-Top Window
I (228) view: Data min[256] = -inf, Data max[1] = 22.490753
 ________________________________________________________________
0|                                                               |
1|                                                               |
2|                                                               |
3|                                                               |
4|                                                               |
5|                                                               |
6|                                                               |
7 ||                                                             |
8   |||||                                                        |
9        |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
 0123456789012345678901234567890123456789012345678901234567890123
I (238) view: Plot: Length=512, min=-120.000000, max=40.000000
I (238) main: End Example.

readme of fir example

FIR Filter Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use FIR filter functionality from esp-dsp library. Example does the following steps:

Initialize the FFT library
Initialize input signal
- 1st Sine wave (f = 0.2Fs)
- 2nd Sine wave (f = 0.4Fs)
- Combine the waves
Show input signal
- Calculate windows coefficients
- Apply the windowing to the input signal
- Do the FFT
- Show the frequency response on a plot
- Calculate execution performance
Show filtered signal
- Initialize the FIR filter library
- Calculate Windowed-Sinc coefficients of FIR filter
- Apply the FIR filter to the input signal
- Do the FFT
- Show the frequency response on a plot
- Calculate execution performance

How to use the example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is a typical example of console output.

I (340) main: Start Example.
I (400) view: Data min[388] = -108.419342, Data max[205] = 30.267143
 ________________________________________________________________
0                         |                         |            |
1                         |                        ||            |
2                         ||                       ||            |
3                         ||                       ||            |
4                         ||                       ||            |
5                         ||                       |||           |
6                       || ||                     |   |          |
7||||||||||||||||||||||||    ||||||||||||||||||||||   ||||||||||||
8                                                                |
9                                                                |
 0123456789012345678901234567890123456789012345678901234567890123
I (470) view: Plot: Length=512, min=-120.000000, max=40.000000


I (490) view: Data min[254] = -114.853371, Data max[205] = 27.247583
 ________________________________________________________________
0                                                   |            |
1                                                  |             |
2                                                  |             |
3                                                  | |           |
4                                                  | |           |
5                                                  | |           |
6                         |                     |||  |||         |
7|||||||||||||||||||||||||||||||||||||||||||||||     |  |||||    |
8                                                            |||||
9                                                                |
 0123456789012345678901234567890123456789012345678901234567890123
I (560) view: Plot: Length=256, min=-120.000000, max=40.000000
I (560) main: FIR for 1024 samples and decimation 2 takes 763647 cycles
I (570) main: End Example.

readme of iir example

IIR Filter Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use IIR filters functionality from esp-dsp library. Example does the following steps:

Initialize the library
Initialize input signal
Show LPF filter with Q factor 1
- Calculate iir filter coefficients
- Filter the input test signal (delta function)
- Shows impulse response on the plot
- Shows frequency response on the plot
- Calculate execution performance
The same for LPF filter with Q factor 10

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (58) main: Start Example.
I (58) main: Impulse response of IIR filter with F=0.100000, qFactor=1.000000
I (68) view: Data min[8] = -0.060052, Data max[2] = 0.333517
 ________________________________________________________________
0                                                                |
1                                                                |
2 -                                                              |
3- -                                                             |
4   -------------------------------------------------------------|
5                                                                |
6                                                                |
7                                                                |
8                                                                |
9                                                                |
 0123456789012345678901234567890123456789012345678901234567890123
I (138) view: Plot: Length=128, min=-1.000000, max=1.000000
I (148) view: Data min[511] = -149.983795, Data max[0] = 0.000000
 ________________________________________________________________
0                                                                |
1                                                                |
2-----------------                                               |
3                 ----------                                     |
4                           -------------                        |
5                                        ----------              |
6                                                  -------       |
7                                                         ---    |
8                                                            --  |
9                                                              --|
 0123456789012345678901234567890123456789012345678901234567890123
I (228) view: Plot: Length=512, min=-100.000000, max=0.000000
I (228) main: IIR for 1024 samples take 20276 cycles
I (238) main: Impulse response of IIR filter with F=0.100000, qFactor=10.000000
I (248) view: Data min[7] = -0.453739, Data max[2] = 0.526114
 ________________________________________________________________
0                                                                |
1                                                                |
2 -    -                                                         |
3- -  - -  ---  ---   -    -                                     |
4- -  - -            - ---- -------------------------------------|
5   --   --   --   --                                            |
6                                                                |
7                                                                |
8                                                                |
9                                                                |
 0123456789012345678901234567890123456789012345678901234567890123
I (318) view: Plot: Length=128, min=-1.000000, max=1.000000
I (328) view: Data min[511] = -149.480377, Data max[0] = 0.000000
 ________________________________________________________________
0            --                                                  |
1          --  -                                                 |
2----------     -----                                            |
3                    --------                                    |
4                            ------------                        |
5                                        ----------              |
6                                                  -------       |
7                                                         ---    |
8                                                            --  |
9                                                              --|
 0123456789012345678901234567890123456789012345678901234567890123
I (408) view: Plot: Length=512, min=-100.000000, max=0.000000
I (408) main: IIR for 1024 samples take 17456 cycles
I (418) main: End Example.

readme of kalman example

Extended Kalman Filter

This example emulate system with IMU sensors and show how to use Extended Kalman Filter (EKF), with 13 values states vector, to estimate gyroscope errors and calculate system attitude. Also, this example show how to use esp-dsp library to operate with matrices and vectors.

In real system, the emulated sensors values should be replace by the real sensors values. Then, in real system, a calibration phase should be implemented and after the calibration phase the state vector X and covariance matrix P should be saved and restored next time, when filter called. It will save time for initial phase.

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example Output

I (380) spi_flash: detected chip: gd
I (383) spi_flash: flash io: dio
W (387) spi_flash: Detected size(4096k) larger than the size in the binary image header(2048k). Using the size in the binary image header.
I (404) cpu_start: Starting scheduler on PRO CPU.
I (0) cpu_start: Starting scheduler on APP CPU.
I (413) main: Start Example.
Gyro error: 0.1 0.2 0.3

Calibration phase started:
Loop 1000 from 48000, State data : 0.998361 0.0152476 0.0211183 0.0509682 0.00463435 0.00919946 0.01352 0.998156 0.00619182 -0.000683098 -0.00117112 0.0063196 -0.000952147
Loop 2000 from 48000, State data : 0.941757 0.0877462 0.170681 0.276156 0.016951 0.0334337 0.0498731 0.998804 0.0162317 -0.00225174 0.00389746 0.0110905 -0.000489083
Loop 3000 from 48000, State data : 0.372216 0.24247 0.488788 0.750832 0.0323164 0.0642265 0.0962768 0.997295 0.0269348 -0.00481966 0.00605674 0.00779719 0.00494921
Loop 4000 from 48000, State data : 0.944725 0.0951798 0.165878 0.266308 0.0470155 0.0946294 0.141251 0.998213 0.0337875 -0.00704064 0.00422252 0.0124181 0.00485692
Loop 5000 from 48000, State data : 0.944287 0.102183 0.168344 0.263706 0.0597481 0.12037 0.179946 0.997498 0.0378795 -0.00841348 0.0053515 0.0104612 0.00666854
Loop 6000 from 48000, State data : 0.379137 0.258284 0.476853 0.74977 0.0697741 0.140876 0.210702 0.995523 0.0410914 -0.00911293 0.00510267 0.00764586 0.00913832
Loop 7000 from 48000, State data : 0.947048 0.112494 0.165382 0.251187 0.0773002 0.156661 0.233985 0.996358 0.0425222 -0.00994576 0.00353348 0.00969652 0.00849919
Loop 8000 from 48000, State data : 0.945556 0.120624 0.169212 0.250481 0.082995 0.16838 0.251493 0.995914 0.0433827 -0.0102827 0.0039165 0.00846988 0.00913964
Loop 9000 from 48000, State data : 0.381034 0.276875 0.4647 0.749805 0.0871785 0.177046 0.264439 0.995073 0.0441243 -0.0103565 0.00391002 0.0071649 0.00997719
Loop 10000 from 48000, State data : 0.946592 0.132375 0.168307 0.241068 0.0902326 0.183443 0.273873 0.995445 0.0443655 -0.0106197 0.00326065 0.00799655 0.00960479
Loop 11000 from 48000, State data : 0.944297 0.140946 0.172816 0.242015 0.0924658 0.188118 0.280807 0.995187 0.0445766 -0.0106806 0.00346742 0.00749049 0.00979064
Loop 12000 from 48000, State data : 0.378334 0.295555 0.452859 0.751285 0.0941005 0.191525 0.285886 0.994796 0.0447763 -0.0106511 0.0034986 0.00695604 0.0100697
Loop 13000 from 48000, State data : 0.944329 0.1532 0.172826 0.234315 0.0953075 0.194011 0.289567 0.994899 0.0448155 -0.0107384 0.00323858 0.00728781 0.00989103
Loop 14000 from 48000, State data : 0.941572 0.16194 0.177533 0.236008 0.0961574 0.195842 0.292257 0.994735 0.0448801 -0.0107422 0.00334282 0.0070798 0.00993131
Loop 15000 from 48000, State data : 0.373427 0.314041 0.441061 0.753256 0.0967899 0.197167 0.294234 0.994523 0.0449438 -0.0107112 0.00335898 0.00685221 0.0100213
Loop 16000 from 48000, State data : 0.941028 0.174338 0.177916 0.228952 0.0972752 0.198121 0.295664 0.994518 0.0449512 -0.0107403 0.0032445 0.00697761 0.00993463
Loop 17000 from 48000, State data : 0.937959 0.183145 0.18262 0.230959 0.0975883 0.198844 0.296697 0.994396 0.0449757 -0.0107339 0.0032963 0.00688409 0.00992845
Loop 18000 from 48000, State data : 0.3675 0.33233 0.429142 0.755207 0.0978324 0.199358 0.297465 0.994256 0.0450002 -0.0107104 0.00330113 0.00677742 0.00995297
Loop 19000 from 48000, State data : 0.937014 0.195546 0.183166 0.224089 0.0980371 0.199716 0.298023 0.994211 0.0450036 -0.0107164 0.00324275 0.00681997 0.00990755
Loop 20000 from 48000, State data : 0.933698 0.204372 0.187784 0.226223 0.0981422 0.200008 0.29842 0.994114 0.0450155 -0.0107065 0.00327025 0.00677405 0.00988484
Loop 21000 from 48000, State data : 0.361055 0.350426 0.417036 0.756916 0.0982358 0.200208 0.29872 0.99401 0.0450272 -0.0106858 0.00326787 0.00671759 0.0098834
Loop 22000 from 48000, State data : 0.932425 0.216717 0.188413 0.219358 0.0983318 0.200334 0.298938 0.993947 0.0450303 -0.0106798 0.00323017 0.00672916 0.00985372
Loop 23000 from 48000, State data : 0.928888 0.225543 0.19291 0.221546 0.0983561 0.200458 0.299082 0.993866 0.0450371 -0.0106664 0.00324701 0.00670354 0.00982584
Loop 24000 from 48000, State data : 0.354297 0.36833 0.404722 0.758292 0.0983915 0.200535 0.299203 0.993773 0.045044 -0.0106443 0.00324109 0.00666712 0.00981608
Loop 25000 from 48000, State data : 0.927316 0.237803 0.19359 0.214612 0.0984453 0.200572 0.299291 0.993709 0.0450468 -0.0106303 0.00321085 0.00666748 0.00979369
Loop 26000 from 48000, State data : 0.92357 0.246618 0.197954 0.216824 0.0984385 0.200632 0.299342 0.993629 0.0450514 -0.0106123 0.00322403 0.00665109 0.00976504
Loop 27000 from 48000, State data : 0.347305 0.386034 0.392194 0.759303 0.0984521 0.200663 0.299393 0.993546 0.0450564 -0.0105864 0.00321847 0.00662376 0.00975319
Loop 28000 from 48000, State data : 0.92171 0.258777 0.198672 0.209796 0.0984898 0.200666 0.299433 0.993475 0.045059 -0.0105663 0.00319366 0.00662077 0.00973562
Loop 29000 from 48000, State data : 0.917761 0.267574 0.202895 0.212019 0.0984714 0.2007 0.299446 0.9934 0.0450631 -0.0105437 0.00320563 0.0066091 0.00970881
Loop 30000 from 48000, State data : 0.340113 0.403531 0.379459 0.759933 0.0984762 0.200711 0.299466 0.993322 0.0450673 -0.0105132 0.00320031 0.00658594 0.00969804
Loop 31000 from 48000, State data : 0.915619 0.279623 0.203648 0.204891 0.0985076 0.2007 0.299484 0.993253 0.0450696 -0.0104878 0.00317637 0.00658294 0.00968329
Loop 32000 from 48000, State data : 0.91147 0.288396 0.207727 0.207121 0.0984838 0.200725 0.299481 0.99318 0.0450732 -0.0104599 0.00318786 0.00657435 0.00965871
Loop 33000 from 48000, State data : 0.332734 0.420812 0.366519 0.760177 0.0984844 0.20073 0.299492 0.993105 0.045077 -0.0104242 0.00318322 0.00655352 0.00964965
Loop 34000 from 48000, State data : 0.909049 0.300327 0.208511 0.199891 0.0985129 0.200714 0.299506 0.993034 0.0450794 -0.0103941 0.0031609 0.00655179 0.00963774
Loop 35000 from 48000, State data : 0.904704 0.309072 0.212442 0.202124 0.0984875 0.200736 0.299498 0.992959 0.0450829 -0.0103612 0.0031732 0.00654506 0.00961709
Loop 36000 from 48000, State data : 0.325179 0.437867 0.353384 0.760034 0.098487 0.200738 0.299504 0.992885 0.0450865 -0.0103208 0.00317079 0.00652607 0.00961171
Loop 37000 from 48000, State data : 0.325177 0.437848 0.353377 0.760049 0.0989011 0.200534 0.299617 0.992838 0.0450912 -0.0103039 0.00319877 0.00652725 0.00959415
Loop 38000 from 48000, State data : 0.325194 0.437821 0.353363 0.760064 0.099202 0.200388 0.299726 0.992838 0.0450926 -0.0102998 0.00320422 0.00652895 0.00959084
Loop 39000 from 48000, State data : 0.325211 0.437798 0.353354 0.760074 0.0994169 0.200278 0.299826 0.992816 0.045093 -0.0102979 0.00320263 0.0065278 0.00959847
Loop 40000 from 48000, State data : 0.325222 0.437784 0.353346 0.760081 0.0995754 0.200199 0.299886 0.992816 0.0450925 -0.0102967 0.00320118 0.00652683 0.00960376
Loop 41000 from 48000, State data : 0.325231 0.437773 0.353342 0.760085 0.0996929 0.200142 0.299945 0.992816 0.0450925 -0.0102966 0.00320043 0.00652627 0.00960631
Loop 42000 from 48000, State data : 0.325238 0.437769 0.353336 0.760087 0.0997802 0.200119 0.299978 0.992816 0.0450913 -0.0102965 0.00320007 0.0065261 0.00960773
Loop 43000 from 48000, State data : 0.32524 0.437762 0.353331 0.760093 0.099842 0.200089 0.299979 0.992816 0.0450913 -0.0102961 0.00320001 0.00652608 0.00960857
Loop 44000 from 48000, State data : 0.325241 0.43776 0.353327 0.760095 0.099883 0.200059 0.299979 0.992816 0.045089 -0.0102953 0.00319975 0.00652622 0.00960868
Loop 45000 from 48000, State data : 0.325243 0.437759 0.353325 0.760096 0.0999138 0.200045 0.299979 0.992816 0.0450878 -0.0102956 0.0031996 0.00652593 0.00960985
Loop 46000 from 48000, State data : 0.325245 0.437756 0.353324 0.760097 0.0999355 0.200042 0.299979 0.992816 0.0450878 -0.0102959 0.00319972 0.0065261 0.00960944
Loop 47000 from 48000, State data : 0.325246 0.437757 0.353322 0.760098 0.0999504 0.200039 0.299979 0.992816 0.0450878 -0.0102959 0.00319952 0.00652634 0.00960984
Calibration phase finished.

Regular calculation started:
Loop 1000 from 48000, State data : 0.9996 6.68374e-06 -7.71055e-05 0.028269 0.0999599 0.199742 0.298758 0.992397 0.0506049 -0.00981295 0.00516875 0.00517689 0.0102406
Loop 2000 from 48000, State data : 0.95186 0.0747648 0.154942 0.253704 0.0997667 0.199899 0.298983 0.992397 0.0504132 -0.0098162 0.00510809 0.00522702 0.0102249
Loop 3000 from 48000, State data : 0.395338 0.237819 0.486861 0.741698 0.0994409 0.200091 0.299095 0.992397 0.0502891 -0.00981838 0.00506923 0.00525921 0.0102147
Loop 4000 from 48000, State data : 0.952465 0.0877289 0.155254 0.247002 0.0992076 0.200299 0.299271 0.992397 0.0502054 -0.00981973 0.00504271 0.00528111 0.0102076
Loop 5000 from 48000, State data : 0.950016 0.096521 0.160702 0.249654 0.0990023 0.200426 0.299306 0.992397 0.05013 -0.00982108 0.00501929 0.00530046 0.0102013
Loop 6000 from 48000, State data : 0.389808 0.256786 0.476033 0.745321 0.0988748 0.200476 0.299331 0.992397 0.050078 -0.00982208 0.0050032 0.00531378 0.0101971
Loop 7000 from 48000, State data : 0.950306 0.109383 0.161046 0.242937 0.0987883 0.200581 0.299444 0.992397 0.0500379 -0.00982289 0.0049906 0.00532416 0.0101938
Loop 8000 from 48000, State data : 0.947646 0.118155 0.166392 0.2456 0.0986931 0.200633 0.299434 0.992397 0.0499987 -0.00982366 0.00497852 0.00533416 0.0101903
Loop 9000 from 48000, State data : 0.383995 0.275557 0.464951 0.748623 0.0986473 0.200627 0.299425 0.992397 0.0499702 -0.00982415 0.00496994 0.00534126 0.0101879
Loop 10000 from 48000, State data : 0.94764 0.130939 0.166769 0.238794 0.0986203 0.200694 0.299509 0.992397 0.0499475 -0.00982454 0.004963 0.00534698 0.0101861
Loop 11000 from 48000, State data : 0.944771 0.139703 0.171999 0.241471 0.0985699 0.200714 0.299481 0.992397 0.0499252 -0.00982467 0.00495605 0.00535274 0.0101844
Loop 12000 from 48000, State data : 0.377949 0.294161 0.453622 0.751566 0.0985571 0.200685 0.299459 0.992397 0.0499092 -0.00982467 0.00495124 0.0053567 0.0101832
Loop 13000 from 48000, State data : 0.944475 0.152413 0.172408 0.234549 0.0985539 0.200736 0.299532 0.992397 0.0498962 -0.00982467 0.00494735 0.0053599 0.0101823
Loop 14000 from 48000, State data : 0.941398 0.16117 0.177516 0.237239 0.0985215 0.200743 0.299498 0.992397 0.0498826 -0.00982467 0.0049434 0.00536316 0.0101813
Loop 15000 from 48000, State data : 0.371694 0.312599 0.442052 0.754132 0.0985222 0.200704 0.299474 0.992397 0.049874 -0.00982467 0.00494084 0.0053653 0.0101808
Loop 16000 from 48000, State data : 0.940819 0.173801 0.177954 0.230187 0.0985277 0.20075 0.299544 0.992397 0.0498671 -0.00982467 0.00493887 0.00536698 0.0101804
Loop 17000 from 48000, State data : 0.937532 0.182552 0.182939 0.232897 0.0985023 0.200752 0.299507 0.992397 0.0498602 -0.00982467 0.0049367 0.0053688 0.0101799
Loop 18000 from 48000, State data : 0.365235 0.33087 0.43025 0.756316 0.0985084 0.200708 0.299482 0.992397 0.0498562 -0.00982467 0.00493555 0.0053698 0.0101796
Loop 19000 from 48000, State data : 0.936669 0.195102 0.183407 0.225717 0.0985175 0.200754 0.299549 0.992397 0.0498532 -0.00982467 0.00493474 0.00537051 0.0101794
Loop 20000 from 48000, State data : 0.933178 0.203841 0.188264 0.22844 0.0984953 0.200754 0.299511 0.992397 0.0498502 -0.00982467 0.00493366 0.00537141 0.010179
Loop 21000 from 48000, State data : 0.35858 0.348967 0.41822 0.758113 0.0985034 0.200709 0.299484 0.992397 0.0498495 -0.00982467 0.00493334 0.00537172 0.0101788
Loop 22000 from 48000, State data : 0.93203 0.216304 0.188763 0.221136 0.0985129 0.200755 0.299549 0.992397 0.0498497 -0.00982467 0.00493327 0.00537182 0.0101787
Loop 23000 from 48000, State data : 0.928336 0.225027 0.193488 0.22387 0.0984918 0.200754 0.29951 0.992397 0.0498497 -0.00982467 0.00493298 0.00537209 0.0101787
Loop 24000 from 48000, State data : 0.351735 0.366882 0.405969 0.759519 0.0985006 0.200707 0.299482 0.992397 0.0498508 -0.00982467 0.00493324 0.00537189 0.0101787
Loop 25000 from 48000, State data : 0.926905 0.237397 0.194017 0.216443 0.0985107 0.200755 0.299545 0.992397 0.0498526 -0.00982467 0.00493366 0.00537159 0.0101787
Loop 26000 from 48000, State data : 0.92301 0.246099 0.198608 0.219185 0.0984902 0.200753 0.299511 0.992397 0.0498537 -0.00982467 0.00493391 0.00537146 0.0101787
Loop 27000 from 48000, State data : 0.344708 0.384605 0.393502 0.760534 0.0984992 0.200706 0.299488 0.992397 0.0498556 -0.00982467 0.00493459 0.00537092 0.0101787
Loop 28000 from 48000, State data : 0.921297 0.258369 0.199166 0.211636 0.0985091 0.200757 0.299555 0.992397 0.0498579 -0.00982467 0.00493535 0.00537033 0.0101787
Loop 29000 from 48000, State data : 0.917204 0.267048 0.203621 0.214385 0.0984891 0.200754 0.29952 0.992397 0.0498601 -0.00982467 0.00493597 0.0053698 0.0101787
Loop 30000 from 48000, State data : 0.337501 0.402129 0.380825 0.761156 0.0984981 0.200706 0.299491 0.992397 0.0498626 -0.00982467 0.00493691 0.00536903 0.0101787
Loop 31000 from 48000, State data : 0.915208 0.279212 0.204208 0.206723 0.0985072 0.200758 0.299553 0.992397 0.0498654 -0.00982467 0.00493789 0.00536824 0.0101787
Loop 32000 from 48000, State data : 0.910918 0.287861 0.208526 0.209479 0.0984873 0.200754 0.299515 0.992397 0.0498676 -0.00982467 0.00493879 0.00536752 0.0101787
Loop 33000 from 48000, State data : 0.330116 0.419445 0.367945 0.761385 0.0984966 0.200704 0.299489 0.992397 0.0498701 -0.00982467 0.00493986 0.00536667 0.0101787
Loop 34000 from 48000, State data : 0.908641 0.299912 0.209141 0.201703 0.0985056 0.200757 0.299551 0.992397 0.0498728 -0.00982467 0.00494093 0.00536582 0.0101787
Loop 35000 from 48000, State data : 0.904158 0.308528 0.213318 0.204462 0.0984862 0.200752 0.299518 0.992397 0.0498751 -0.00982467 0.00494188 0.00536507 0.0101787
Loop 36000 from 48000, State data : 0.322561 0.436541 0.354869 0.761219 0.0984953 0.200702 0.299495 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 37000 from 48000, State data : 0.322549 0.436508 0.354868 0.761243 0.0989076 0.200506 0.299634 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 38000 from 48000, State data : 0.322568 0.436485 0.354851 0.761257 0.099208 0.200371 0.299726 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 39000 from 48000, State data : 0.322581 0.436466 0.354841 0.761267 0.0994207 0.200267 0.299799 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 40000 from 48000, State data : 0.322592 0.436454 0.354831 0.761274 0.099581 0.200208 0.299849 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 41000 from 48000, State data : 0.322601 0.436443 0.354826 0.761278 0.099701 0.20015 0.299901 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 42000 from 48000, State data : 0.322606 0.436435 0.35482 0.761283 0.0997844 0.200101 0.299931 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 43000 from 48000, State data : 0.322611 0.436429 0.35482 0.761285 0.0998457 0.200072 0.299961 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 44000 from 48000, State data : 0.322615 0.436425 0.354818 0.761286 0.0998883 0.200057 0.29999 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 45000 from 48000, State data : 0.322617 0.436423 0.354816 0.761287 0.099912 0.200042 0.300002 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 46000 from 48000, State data : 0.322617 0.436421 0.354815 0.761289 0.0999343 0.20003 0.300002 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Loop 47000 from 48000, State data : 0.322618 0.436421 0.354814 0.761289 0.0999444 0.20003 0.300002 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Final State data : 0.322618 0.436421 0.354814 0.761289 0.0999518 0.20003 0.300002 0.992397 0.0498778 -0.00982467 0.00494296 0.00536423 0.0101787
Estimated error : 0.0999518 0.20003 0.300002
Difference between real and estimated errors : 4.81904e-05 -2.99811e-05 -2.17557e-06

Expected Euler angels (degree) : -29.8215 64.9692 150.241
Calculated Euler angels (degree) : -35.1525 63.3067 156.167

readme of matrix example

Matrix Operations Example

(See the README.md file in the upper level 'examples' directory for more information about examples.)

This example demonstrates how to use Mat class functionality from esp-dsp library. Example does the following steps:

Initialize a matrix A and matirx x
Calculate matrix b: b = A*x
Find roots x1_: A*x1_ = b, with different methods
Print result

How to use example

Hardware required

This example does not require any special hardware, and can be run on any common development board.

Configure the project

Under Component Config ---> DSP Library ---> DSP Optimization, it's possible to choose either the optimized or ANSI implementation, to compare them.

Build and flash

Build the project and flash it to the board, then run monitor tool to view serial output (replace PORT with serial port name):

idf.py -p PORT flash monitor

(To exit the serial monitor, type Ctrl-].)

See the Getting Started Guide for full steps to configure and use ESP-IDF to build projects.

Example output

Here is an typical example console output.

I (215) main: Start Example.
I (215) main: Original vector x:
0
1
2
I (215) main: Solve result:
0
1
2
I (215) main: Roots result:
0
1
2
I (215) main: End Example.

espressif/esp-dsp 1.4.0 1.3.5 1.3.4 1.3.3 1.3.1 1.3.0 1.2.1 1.2.0 1.1.0 1.0.0 Install

readme

Espressif DSP Library

Overview

Documentation

Installation and Usage

Adding ESP-DSP component to an existing project

Downloading ESP-DSP examples

Building and running ESP-DSP examples

Reporting Issues

Contributing to ESP-DSP

Copyrights and License

changelog

Esp-dsp Changelog

[1.4.0] 2023-05-29

Added

Fixed

Changed

Removed

[1.3.0] 2023-03-10

Added

Fixed

Changed

Removed

[1.2.0] 2022-09-22

readme of basic_math example

Basic Math Example

How to use example

Hardware required

Configure the project

Build and flash

Example output

readme of dotprod example

Dot Product Calculation Example

How to use example

Hardware required

Configure the project

Build and flash

Example output

readme of fft example

FFT Example

How to use example

Hardware required

Configure the project

Build and flash

Example output

readme of fft4real example

FFT 4 Real Input Example

How to use example

Hardware required

Configure the project

Build and flash

Example output

readme of fft_window example

FFT Window Example

How to use example

Hardware required

Configure the project

Build and flash

Example output

readme of fir example

FIR Filter Example

How to use the example

Hardware required

Configure the project

Build and flash

Example output

readme of iir example

IIR Filter Example

How to use example

Hardware required

Configure the project

Build and flash

Example output

readme of kalman example

Extended Kalman Filter

How to use example

Hardware required

Configure the project

Build and flash

espressif/esp-dsp

1.3.5

1.3.4

1.3.3

1.3.1

1.3.0

1.2.1

1.2.0

1.1.0

1.0.0