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Diffstat (limited to 'DSP_Lib/Examples/arm_convolution_example/ARM/arm_convolution_example_f32.c')
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diff --git a/DSP_Lib/Examples/arm_convolution_example/ARM/arm_convolution_example_f32.c b/DSP_Lib/Examples/arm_convolution_example/ARM/arm_convolution_example_f32.c deleted file mode 100644 index 00b0213..0000000 --- a/DSP_Lib/Examples/arm_convolution_example/ARM/arm_convolution_example_f32.c +++ /dev/null @@ -1,247 +0,0 @@ -/* ---------------------------------------------------------------------- -* 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, <code>a[n]</code> and <code>b[n]</code>, 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 <code>(n1+n2-1)</code> - * and is a power of 4 as FFT implementation is radix-4. - * The convolution of <code>a[n]</code> and <code>b[n]</code> 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: - * <pre> A[k] = FFT(a[n],N) - * B[k] = FFT(b[n],N) - * conv(a[n], b[n]) = IFFT(A[k] * B[k], N)</pre> - * where <code>A[k]</code> and <code>B[k]</code> are the N-point FFTs of the signals <code>a[n]</code> - * and <code>b[n]</code> respectively. - * The length of the convolved signal is <code>(n1+n2-1)</code>. - * - * \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, <code>(srcALen + srcBLen - 1)</code> - * \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() - * - * <b> Refer </b> - * \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 */ |