From 6ab94e0b318884bbcb95e2ea3835f951502e1d99 Mon Sep 17 00:00:00 2001 From: jaseg Date: Wed, 14 Oct 2020 12:47:28 +0200 Subject: Move firmware into subdirectory --- .../arm_convolution_example_f32.c | 247 +++++++++++++++++++++ 1 file changed, 247 insertions(+) create mode 100644 fw/midi-dials/Drivers/CMSIS/DSP/Examples/ARM/arm_convolution_example/arm_convolution_example_f32.c (limited to 'fw/midi-dials/Drivers/CMSIS/DSP/Examples/ARM/arm_convolution_example/arm_convolution_example_f32.c') diff --git a/fw/midi-dials/Drivers/CMSIS/DSP/Examples/ARM/arm_convolution_example/arm_convolution_example_f32.c b/fw/midi-dials/Drivers/CMSIS/DSP/Examples/ARM/arm_convolution_example/arm_convolution_example_f32.c new file mode 100644 index 0000000..e4665fe --- /dev/null +++ b/fw/midi-dials/Drivers/CMSIS/DSP/Examples/ARM/arm_convolution_example/arm_convolution_example_f32.c @@ -0,0 +1,247 @@ +/* ---------------------------------------------------------------------- +* Copyright (C) 2010-2012 ARM Limited. All rights reserved. +* +* $Date: 17. January 2013 +* $Revision: V1.4.0 +* +* Project: CMSIS DSP Library +* Title: arm_convolution_example_f32.c +* +* Description: Example code demonstrating Convolution of two input signals using fft. +* +* Target Processor: Cortex-M4/Cortex-M3 +* +* Redistribution and use in source and binary forms, with or without +* modification, are permitted provided that the following conditions +* are met: +* - Redistributions of source code must retain the above copyright +* notice, this list of conditions and the following disclaimer. +* - Redistributions in binary form must reproduce the above copyright +* notice, this list of conditions and the following disclaimer in +* the documentation and/or other materials provided with the +* distribution. +* - Neither the name of ARM LIMITED nor the names of its contributors +* may be used to endorse or promote products derived from this +* software without specific prior written permission. +* +* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS +* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE +* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, +* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, +* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT +* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN +* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +* POSSIBILITY OF SUCH DAMAGE. +* -------------------------------------------------------------------- */ + +/** + * @ingroup groupExamples + */ + +/** + * @defgroup ConvolutionExample Convolution Example + * + * \par Description: + * \par + * Demonstrates the convolution theorem with the use of the Complex FFT, Complex-by-Complex + * Multiplication, and Support Functions. + * + * \par Algorithm: + * \par + * The convolution theorem states that convolution in the time domain corresponds to + * multiplication in the frequency domain. Therefore, the Fourier transform of the convoution of + * two signals is equal to the product of their individual Fourier transforms. + * The Fourier transform of a signal can be evaluated efficiently using the Fast Fourier Transform (FFT). + * \par + * Two input signals, a[n] and b[n], with lengths \c n1 and \c n2 respectively, + * are zero padded so that their lengths become \c N, which is greater than or equal to (n1+n2-1) + * and is a power of 4 as FFT implementation is radix-4. + * The convolution of a[n] and b[n] is obtained by taking the FFT of the input + * signals, multiplying the Fourier transforms of the two signals, and taking the inverse FFT of + * the multiplied result. + * \par + * This is denoted by the following equations: + * 
 A[k] = FFT(a[n],N)
+ * B[k] = FFT(b[n],N)
+ * conv(a[n], b[n]) = IFFT(A[k] * B[k], N)
+ * where A[k] and B[k] are the N-point FFTs of the signals a[n] + * and b[n] respectively. + * The length of the convolved signal is (n1+n2-1). + * + * \par Block Diagram: + * \par + * \image html Convolution.gif + * + * \par Variables Description: + * \par + * \li \c testInputA_f32 points to the first input sequence + * \li \c srcALen length of the first input sequence + * \li \c testInputB_f32 points to the second input sequence + * \li \c srcBLen length of the second input sequence + * \li \c outLen length of convolution output sequence, (srcALen + srcBLen - 1) + * \li \c AxB points to the output array where the product of individual FFTs of inputs is stored. + * + * \par CMSIS DSP Software Library Functions Used: + * \par + * - arm_fill_f32() + * - arm_copy_f32() + * - arm_cfft_radix4_init_f32() + * - arm_cfft_radix4_f32() + * - arm_cmplx_mult_cmplx_f32() + * + * Refer + * \link arm_convolution_example_f32.c \endlink + * + */ + + +/** \example arm_convolution_example_f32.c + */ + +#include "arm_math.h" +#include "math_helper.h" + +/* ---------------------------------------------------------------------- +* Defines each of the tests performed +* ------------------------------------------------------------------- */ +#define MAX_BLOCKSIZE 128 +#define DELTA (0.000001f) +#define SNR_THRESHOLD 90 + +/* ---------------------------------------------------------------------- +* Declare I/O buffers +* ------------------------------------------------------------------- */ +float32_t Ak[MAX_BLOCKSIZE]; /* Input A */ +float32_t Bk[MAX_BLOCKSIZE]; /* Input B */ +float32_t AxB[MAX_BLOCKSIZE * 2]; /* Output */ + +/* ---------------------------------------------------------------------- +* Test input data for Floating point Convolution example for 32-blockSize +* Generated by the MATLAB randn() function +* ------------------------------------------------------------------- */ +float32_t testInputA_f32[64] = +{ + -0.808920, 1.357369, 1.180861, -0.504544, 1.762637, -0.703285, + 1.696966, 0.620571, -0.151093, -0.100235, -0.872382, -0.403579, + -0.860749, -0.382648, -1.052338, 0.128113, -0.646269, 1.093377, + -2.209198, 0.471706, 0.408901, 1.266242, 0.598252, 1.176827, + -0.203421, 0.213596, -0.851964, -0.466958, 0.021841, -0.698938, + -0.604107, 0.461778, -0.318219, 0.942520, 0.577585, 0.417619, + 0.614665, 0.563679, -1.295073, -0.764437, 0.952194, -0.859222, + -0.618554, -2.268542, -1.210592, 1.655853, -2.627219, -0.994249, + -1.374704, 0.343799, 0.025619, 1.227481, -0.708031, 0.069355, + -1.845228, -1.570886, 1.010668, -1.802084, 1.630088, 1.286090, + -0.161050, -0.940794, 0.367961, 0.291907 + +}; + +float32_t testInputB_f32[64] = +{ + 0.933724, 0.046881, 1.316470, 0.438345, 0.332682, 2.094885, + 0.512081, 0.035546, 0.050894, -2.320371, 0.168711, -1.830493, + -0.444834, -1.003242, -0.531494, -1.365600, -0.155420, -0.757692, + -0.431880, -0.380021, 0.096243, -0.695835, 0.558850, -1.648962, + 0.020369, -0.363630, 0.887146, 0.845503, -0.252864, -0.330397, + 1.269131, -1.109295, -1.027876, 0.135940, 0.116721, -0.293399, + -1.349799, 0.166078, -0.802201, 0.369367, -0.964568, -2.266011, + 0.465178, 0.651222, -0.325426, 0.320245, -0.784178, -0.579456, + 0.093374, 0.604778, -0.048225, 0.376297, -0.394412, 0.578182, + -1.218141, -1.387326, 0.692462, -0.631297, 0.153137, -0.638952, + 0.635474, -0.970468, 1.334057, -0.111370 +}; + +const float testRefOutput_f32[127] = +{ + -0.818943, 1.229484, -0.533664, 1.016604, 0.341875, -1.963656, + 5.171476, 3.478033, 7.616361, 6.648384, 0.479069, 1.792012, + -1.295591, -7.447818, 0.315830, -10.657445, -2.483469, -6.524236, + -7.380591, -3.739005, -8.388957, 0.184147, -1.554888, 3.786508, + -1.684421, 5.400610, -1.578126, 7.403361, 8.315999, 2.080267, + 11.077776, 2.749673, 7.138962, 2.748762, 0.660363, 0.981552, + 1.442275, 0.552721, -2.576892, 4.703989, 0.989156, 8.759344, + -0.564825, -3.994680, 0.954710, -5.014144, 6.592329, 1.599488, + -13.979146, -0.391891, -4.453369, -2.311242, -2.948764, 1.761415, + -0.138322, 10.433007, -2.309103, 4.297153, 8.535523, 3.209462, + 8.695819, 5.569919, 2.514304, 5.582029, 2.060199, 0.642280, + 7.024616, 1.686615, -6.481756, 1.343084, -3.526451, 1.099073, + -2.965764, -0.173723, -4.111484, 6.528384, -6.965658, 1.726291, + 1.535172, 11.023435, 2.338401, -4.690188, 1.298210, 3.943885, + 8.407885, 5.168365, 0.684131, 1.559181, 1.859998, 2.852417, + 8.574070, -6.369078, 6.023458, 11.837963, -6.027632, 4.469678, + -6.799093, -2.674048, 6.250367, -6.809971, -3.459360, 9.112410, + -2.711621, -1.336678, 1.564249, -1.564297, -1.296760, 8.904013, + -3.230109, 6.878013, -7.819823, 3.369909, -1.657410, -2.007358, + -4.112825, 1.370685, -3.420525, -6.276605, 3.244873, -3.352638, + 1.545372, 0.902211, 0.197489, -1.408732, 0.523390, 0.348440, 0 +}; + + +/* ---------------------------------------------------------------------- +* Declare Global variables +* ------------------------------------------------------------------- */ +uint32_t srcALen = 64; /* Length of Input A */ +uint32_t srcBLen = 64; /* Length of Input B */ +uint32_t outLen; /* Length of convolution output */ +float32_t snr; /* output SNR */ + +int32_t main(void) +{ + arm_status status; /* Status of the example */ + arm_cfft_radix4_instance_f32 cfft_instance; /* CFFT Structure instance */ + + /* CFFT Structure instance pointer */ + arm_cfft_radix4_instance_f32 *cfft_instance_ptr = + (arm_cfft_radix4_instance_f32*) &cfft_instance; + + /* output length of convolution */ + outLen = srcALen + srcBLen - 1; + + /* Initialise the fft input buffers with all zeros */ + arm_fill_f32(0.0, Ak, MAX_BLOCKSIZE); + arm_fill_f32(0.0, Bk, MAX_BLOCKSIZE); + + /* Copy the input values to the fft input buffers */ + arm_copy_f32(testInputA_f32, Ak, MAX_BLOCKSIZE/2); + arm_copy_f32(testInputB_f32, Bk, MAX_BLOCKSIZE/2); + + /* Initialize the CFFT function to compute 64 point fft */ + status = arm_cfft_radix4_init_f32(cfft_instance_ptr, 64, 0, 1); + + /* Transform input a[n] from time domain to frequency domain A[k] */ + arm_cfft_radix4_f32(cfft_instance_ptr, Ak); + /* Transform input b[n] from time domain to frequency domain B[k] */ + arm_cfft_radix4_f32(cfft_instance_ptr, Bk); + + /* Complex Multiplication of the two input buffers in frequency domain */ + arm_cmplx_mult_cmplx_f32(Ak, Bk, AxB, MAX_BLOCKSIZE/2); + + /* Initialize the CIFFT function to compute 64 point ifft */ + status = arm_cfft_radix4_init_f32(cfft_instance_ptr, 64, 1, 1); + + /* Transform the multiplication output from frequency domain to time domain, + that gives the convolved output */ + arm_cfft_radix4_f32(cfft_instance_ptr, AxB); + + /* SNR Calculation */ + snr = arm_snr_f32((float32_t *)testRefOutput_f32, AxB, srcALen + srcBLen - 1); + + /* Compare the SNR with threshold to test whether the + computed output is matched with the reference output values. */ + if ( snr > SNR_THRESHOLD) + { + status = ARM_MATH_SUCCESS; + } + + if ( status != ARM_MATH_SUCCESS) + { + while (1); + } + + while (1); /* main function does not return */ +} + + /** \endlink */ -- cgit