TM STM32Fxxx HAL Libraries  v1.0.0 Libraries for STM32Fxxx (F0, F4 and F7 series) devices based on HAL drivers from ST from Tilen Majerle

FFT library for STM32Fxxx devices - http://stm32f4-discovery.com/2015/07/hal-library-14-fast-fourier-transform-for-stm32fxxx/. More...

## Modules

TM_FFT_Macros
Library defines.

TM_FFT_Typedefs
Library Typedefs.

TM_FFT_Functions
Library Functions.

## Detailed Description

FFT library for STM32Fxxx devices - http://stm32f4-discovery.com/2015/07/hal-library-14-fast-fourier-transform-for-stm32fxxx/.

This library allows you to calculate FFT in your signal.

For more info about FFT and how it works on Cortex-M4, you should take a look at ARM DSP documentation.

ARM dependencies

Some libraries are needed in order to start with ARM CMSIS MATH Library.

- arm_const_structs.c, available in “CMSIS\DSP_Lib\Source\CommonTables”
- arm_cortexM4lf_math.lib for ARM compiler, available in “CMSIS\Lib\ARM”
- CMSIS folder can be found if you download these libraries directly from ARM.com or if you download Standard Perihperal Drivers for STM32F4xx from ST.com site.

ARM MATH

ARM MATH is a library provided from ARM and is the same for all Cortex families, except that you have to provide some informations to library.

//Use ARM MATH for Cortex-M4
#define ARM_MATH_CM4
//Use ARM MATH for Cortex-M7
#define ARM_MATH_CM7
//Use ARM MATH for Cortex-M0
#define ARM_MATH_CM0
//Use ARM MATH for Cortex-M0+
#define ARM_MATH_CM0PLUS
//Set define if FPU presents on device. On F4xx and F7xx it is available
#define __FPU_PRESENT 1
FFT Samples count

ARM FFT library allows you to use specific number of samples for data calculation.

These values can be every number which is power of 2 from 2^4 and 2^12. So, 9 different FFT length options. This number is passed into function when you initialize FFT with TM_FFT_Init_F32.

FFT input/output buffers

FFT works in a way that you first fill input buffer with samples and then you process them and you got samples in output buffer. Complex (CFFT) Fast Fourier Transform, which is also used behind the scenes in my library so uses real and imaginary part in input buffer and only real part is calculated to output buffer.

For this reason, input buffer HAVE TO be 2 * FFT_Size in length and output buffer HAVE TO be FFT_Size in length where FFT_Size is the same as FFT_Samples count explained above.

Library is able to use malloc() to allocate memory for you. You just need to enable this feature when you initialize FFT module and everything will be done for you.

Note
You have to make sure that you have enough HEAP memory available for malloc, otherwise malloc will fail and you will not get anything.

For example, if you have 512 length FFT size, then input buffer must be 2 * 512 = 1024 samples of float 32 and output buffer is 512 samples of float 32. In common, this is 1536 samples of float32 which is 4-bytes long in memory. Together this would be 6144 Bytes of HEAP memory.

Changelog
 Version 1.0
- First release

Dependencies
 - STM32Fxxx HAL
- defines.h
- ARM MATH
- ARM CONST STRUCTS