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+/* ----------------------------------------------------------------------
+* Copyright (C) 2010-2012 ARM Limited. All rights reserved.
+*
+* $Date: 17. January 2013
+* $Revision: V1.4.0
+*
+* Project: CMSIS DSP Library
+* Title: arm_matrix_example_f32.c
+*
+* Description: Example code demonstrating least square fit to data
+* using matrix functions
+*
+* 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 MatrixExample Matrix Example
+ *
+ * \par Description:
+ * \par
+ * Demonstrates the use of Matrix Transpose, Matrix Muliplication, and Matrix Inverse
+ * functions to apply least squares fitting to input data. Least squares fitting is
+ * the procedure for finding the best-fitting curve that minimizes the sum of the
+ * squares of the offsets (least square error) from a given set of data.
+ *
+ * \par Algorithm:
+ * \par
+ * The linear combination of parameters considered is as follows:
+ * \par
+ * <code>A * X = B</code>, where \c X is the unknown value and can be estimated
+ * from \c A & \c B.
+ * \par
+ * The least squares estimate \c X is given by the following equation:
+ * \par
+ * <code>X = Inverse(A<sup>T</sup> * A) * A<sup>T</sup> * B</code>
+ *
+ * \par Block Diagram:
+ * \par
+ * \image html matrixExample.gif
+ *
+ * \par Variables Description:
+ * \par
+ * \li \c A_f32 input matrix in the linear combination equation
+ * \li \c B_f32 output matrix in the linear combination equation
+ * \li \c X_f32 unknown matrix estimated using \c A_f32 & \c B_f32 matrices
+ *
+ * \par CMSIS DSP Software Library Functions Used:
+ * \par
+ * - arm_mat_init_f32()
+ * - arm_mat_trans_f32()
+ * - arm_mat_mult_f32()
+ * - arm_mat_inverse_f32()
+ *
+ * <b> Refer </b>
+ * \link arm_matrix_example_f32.c \endlink
+ *
+ */
+
+
+/** \example arm_matrix_example_f32.c
+ */
+
+#include "arm_math.h"
+#include "math_helper.h"
+
+#define SNR_THRESHOLD 90
+
+/* --------------------------------------------------------------------------------
+* Test input data(Cycles) taken from FIR Q15 module for differant cases of blockSize
+* and tapSize
+* --------------------------------------------------------------------------------- */
+
+const float32_t B_f32[4] =
+{
+ 782.0, 7577.0, 470.0, 4505.0
+};
+
+/* --------------------------------------------------------------------------------
+* Formula to fit is C1 + C2 * numTaps + C3 * blockSize + C4 * numTaps * blockSize
+* -------------------------------------------------------------------------------- */
+
+const float32_t A_f32[16] =
+{
+ /* Const, numTaps, blockSize, numTaps*blockSize */
+ 1.0, 32.0, 4.0, 128.0,
+ 1.0, 32.0, 64.0, 2048.0,
+ 1.0, 16.0, 4.0, 64.0,
+ 1.0, 16.0, 64.0, 1024.0,
+};
+
+
+/* ----------------------------------------------------------------------
+* Temporary buffers for storing intermediate values
+* ------------------------------------------------------------------- */
+/* Transpose of A Buffer */
+float32_t AT_f32[16];
+/* (Transpose of A * A) Buffer */
+float32_t ATMA_f32[16];
+/* Inverse(Transpose of A * A) Buffer */
+float32_t ATMAI_f32[16];
+/* Test Output Buffer */
+float32_t X_f32[4];
+
+/* ----------------------------------------------------------------------
+* Reference ouput buffer C1, C2, C3 and C4 taken from MATLAB
+* ------------------------------------------------------------------- */
+const float32_t xRef_f32[4] = {73.0, 8.0, 21.25, 2.875};
+
+float32_t snr;
+
+
+/* ----------------------------------------------------------------------
+* Max magnitude FFT Bin test
+* ------------------------------------------------------------------- */
+
+int32_t main(void)
+{
+
+ arm_matrix_instance_f32 A; /* Matrix A Instance */
+ arm_matrix_instance_f32 AT; /* Matrix AT(A transpose) instance */
+ arm_matrix_instance_f32 ATMA; /* Matrix ATMA( AT multiply with A) instance */
+ arm_matrix_instance_f32 ATMAI; /* Matrix ATMAI(Inverse of ATMA) instance */
+ arm_matrix_instance_f32 B; /* Matrix B instance */
+ arm_matrix_instance_f32 X; /* Matrix X(Unknown Matrix) instance */
+
+ uint32_t srcRows, srcColumns; /* Temporary variables */
+ arm_status status;
+
+ /* Initialise A Matrix Instance with numRows, numCols and data array(A_f32) */
+ srcRows = 4;
+ srcColumns = 4;
+ arm_mat_init_f32(&A, srcRows, srcColumns, (float32_t *)A_f32);
+
+ /* Initialise Matrix Instance AT with numRows, numCols and data array(AT_f32) */
+ srcRows = 4;
+ srcColumns = 4;
+ arm_mat_init_f32(&AT, srcRows, srcColumns, AT_f32);
+
+ /* calculation of A transpose */
+ status = arm_mat_trans_f32(&A, &AT);
+
+
+ /* Initialise ATMA Matrix Instance with numRows, numCols and data array(ATMA_f32) */
+ srcRows = 4;
+ srcColumns = 4;
+ arm_mat_init_f32(&ATMA, srcRows, srcColumns, ATMA_f32);
+
+ /* calculation of AT Multiply with A */
+ status = arm_mat_mult_f32(&AT, &A, &ATMA);
+
+ /* Initialise ATMAI Matrix Instance with numRows, numCols and data array(ATMAI_f32) */
+ srcRows = 4;
+ srcColumns = 4;
+ arm_mat_init_f32(&ATMAI, srcRows, srcColumns, ATMAI_f32);
+
+ /* calculation of Inverse((Transpose(A) * A) */
+ status = arm_mat_inverse_f32(&ATMA, &ATMAI);
+
+ /* calculation of (Inverse((Transpose(A) * A)) * Transpose(A)) */
+ status = arm_mat_mult_f32(&ATMAI, &AT, &ATMA);
+
+ /* Initialise B Matrix Instance with numRows, numCols and data array(B_f32) */
+ srcRows = 4;
+ srcColumns = 1;
+ arm_mat_init_f32(&B, srcRows, srcColumns, (float32_t *)B_f32);
+
+ /* Initialise X Matrix Instance with numRows, numCols and data array(X_f32) */
+ srcRows = 4;
+ srcColumns = 1;
+ arm_mat_init_f32(&X, srcRows, srcColumns, X_f32);
+
+ /* calculation ((Inverse((Transpose(A) * A)) * Transpose(A)) * B) */
+ status = arm_mat_mult_f32(&ATMA, &B, &X);
+
+ /* Comparison of reference with test output */
+ snr = arm_snr_f32((float32_t *)xRef_f32, X_f32, 4);
+
+ /*------------------------------------------------------------------------------
+ * Initialise status depending on SNR calculations
+ *------------------------------------------------------------------------------*/
+ if ( snr > SNR_THRESHOLD)
+ {
+ status = ARM_MATH_SUCCESS;
+ }
+ else
+ {
+ status = ARM_MATH_TEST_FAILURE;
+ }
+
+
+ /* ----------------------------------------------------------------------
+ ** Loop here if the signals fail the PASS check.
+ ** This denotes a test failure
+ ** ------------------------------------------------------------------- */
+ if ( status != ARM_MATH_SUCCESS)
+ {
+ while (1);
+ }
+
+ while (1); /* main function does not return */
+}
+
+ /** \endlink */