k60-keil

K60-Keil版本（下载安装MDK4.23）

/* ----------------------------------------------------------------------   
* Copyright (C) 2010 ARM Limited. All rights reserved.   
*   
* $Date:        15. July 2011  
* $Revision: 	V1.0.10  
*   
* Project: 	    CMSIS DSP Library   
* Title:	    arm_fir_lattice_f32.c   
*   
* Description:	Processing function for the floating-point FIR Lattice filter.   
*   
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*  
* Version 1.0.10 2011/7/15 
*    Big Endian support added and Merged M0 and M3/M4 Source code.  
*   
* Version 1.0.3 2010/11/29  
*    Re-organized the CMSIS folders and updated documentation.   
*    
* Version 1.0.2 2010/11/11   
*    Documentation updated.    
*   
* Version 1.0.1 2010/10/05    
*    Production release and review comments incorporated.   
*   
* Version 1.0.0 2010/09/20    
*    Production release and review comments incorporated   
*   
* Version 0.0.7  2010/06/10    
*    Misra-C changes done   
* -------------------------------------------------------------------- */

#include "arm_math.h"

/**   
 * @ingroup groupFilters   
 */

/**   
 * @defgroup FIR_Lattice Finite Impulse Response (FIR) Lattice Filters   
 *   
 * This set of functions implements Finite Impulse Response (FIR) lattice filters   
 * for Q15, Q31 and floating-point data types.  Lattice filters are used in a    
 * variety of adaptive filter applications.  The filter structure is feedforward and   
 * the net impulse response is finite length.   
 * The functions operate on blocks   
 * of input and output data and each call to the function processes   
 * <code>blockSize</code> samples through the filter.  <code>pSrc</code> and   
 * <code>pDst</code> point to input and output arrays containing <code>blockSize</code> values.   
 *   
 * \par Algorithm:   
 * \image html FIRLattice.gif "Finite Impulse Response Lattice filter"   
 * The following difference equation is implemented:   
 * <pre>   
 *    f0[n] = g0[n] = x[n]   
 *    fm[n] = fm-1[n] + km * gm-1[n-1] for m = 1, 2, ...M   
 *    gm[n] = km * fm-1[n] + gm-1[n-1] for m = 1, 2, ...M   
 *    y[n] = fM[n]   
 * </pre>   
 * \par   
 * <code>pCoeffs</code> points to tha array of reflection coefficients of size <code>numStages</code>.   
 * Reflection Coefficients are stored in the following order.   
 * \par   
 * <pre>   
 *    {k1, k2, ..., kM}   
 * </pre>   
 * where M is number of stages   
 * \par   
 * <code>pState</code> points to a state array of size <code>numStages</code>.   
 * The state variables (g values) hold previous inputs and are stored in the following order.   
 * <pre>   
 *    {g0[n], g1[n], g2[n] ...gM-1[n]}   
 * </pre>   
 * The state variables are updated after each block of data is processed; the coefficients are untouched.   
 * \par Instance Structure   
 * The coefficients and state variables for a filter are stored together in an instance data structure.   
 * A separate instance structure must be defined for each filter.   
 * Coefficient arrays may be shared among several instances while state variable arrays cannot be shared.   
 * There are separate instance structure declarations for each of the 3 supported data types.   
 *   
 * \par Initialization Functions   
 * There is also an associated initialization function for each data type.   
 * The initialization function performs the following operations:   
 * - Sets the values of the internal structure fields.   
 * - Zeros out the values in the state buffer.   
 *   
 * \par   
 * Use of the initialization function is optional.   
 * However, if the initialization function is used, then the instance structure cannot be placed into a const data section.   
 * To place an instance structure into a const data section, the instance structure must be manually initialized.   
 * Set the values in the state buffer to zeros and then manually initialize the instance structure as follows:   
 * <pre>   
 *arm_fir_lattice_instance_f32 S = {numStages, pState, pCoeffs};   
 *arm_fir_lattice_instance_q31 S = {numStages, pState, pCoeffs};   
 *arm_fir_lattice_instance_q15 S = {numStages, pState, pCoeffs};   
 * </pre>   
 * \par   
 * where <code>numStages</code> is the number of stages in the filter; <code>pState</code> is the address of the state buffer;   
 * <code>pCoeffs</code> is the address of the coefficient buffer.   
 * \par Fixed-Point Behavior   
 * Care must be taken when using the fixed-point versions of the FIR Lattice filter functions.   
 * In particular, the overflow and saturation behavior of the accumulator used in each function must be considered.   
 * Refer to the function specific documentation below for usage guidelines.   
 */

/**   
 * @addtogroup FIR_Lattice   
 * @{   
 */


  /**   
   * @brief Processing function for the floating-point FIR lattice filter.   
   * @param[in]  *S        points to an instance of the floating-point FIR lattice structure.   
   * @param[in]  *pSrc     points to the block of input data.   
   * @param[out] *pDst     points to the block of output data   
   * @param[in]  blockSize number of samples to process.   
   * @return none.   
   */

void arm_fir_lattice_f32(
  const arm_fir_lattice_instance_f32 * S,
  float32_t * pSrc,
  float32_t * pDst,
  uint32_t blockSize)
{
  float32_t *pState;                             /* State pointer */
  float32_t *pCoeffs = S->pCoeffs;               /* Coefficient pointer */
  float32_t *px;                                 /* temporary state pointer */
  float32_t *pk;                                 /* temporary coefficient pointer */


#ifndef ARM_MATH_CM0

  /* Run the below code for Cortex-M4 and Cortex-M3 */

  float32_t fcurr1, fnext1, gcurr1, gnext1;      /* temporary variables for first sample in loop unrolling */
  float32_t fcurr2, fnext2, gnext2;              /* temporary variables for second sample in loop unrolling */
  float32_t fcurr3, fnext3, gnext3;              /* temporary variables for third sample in loop unrolling */
  float32_t fcurr4, fnext4, gnext4;              /* temporary variables for fourth sample in loop unrolling */
  uint32_t numStages = S->numStages;             /* Number of stages in the filter */
  uint32_t blkCnt, stageCnt;                     /* temporary variables for counts */

  gcurr1 = 0.0f;
  pState = &S->pState[0];

  blkCnt = blockSize >> 2;

  /* First part of the processing with loop unrolling.  Compute 4 outputs at a time.   
     a second loop below computes the remaining 1 to 3 samples. */
  while(blkCnt > 0u)
  {

    /* Read two samples from input buffer */
    /* f0(n) = x(n) */
    fcurr1 = *pSrc++;
    fcurr2 = *pSrc++;

    /* Initialize coeff pointer */
    pk = (pCoeffs);

    /* Initialize state pointer */
    px = pState;

    /* Read g0(n-1) from state */
    gcurr1 = *px;

    /* Process first sample for first tap */
    /* f1(n) = f0(n) +  K1 * g0(n-1) */
    fnext1 = fcurr1 + ((*pk) * gcurr1);
    /* g1(n) = f0(n) * K1  +  g0(n-1) */
    gnext1 = (fcurr1 * (*pk)) + gcurr1;

    /* Process second sample for first tap */
    /* for sample 2 processing */
    fnext2 = fcurr2 + ((*pk) * fcurr1);
    gnext2 = (fcurr2 * (*pk)) + fcurr1;

    /* Read next two samples from input buffer */
    /* f0(n+2) = x(n+2) */
    fcurr3 = *pSrc++;
    fcurr4 = *pSrc++;

    /* Copy only last input samples into the state buffer   
       which will be used for next four samples processing */
    *px++ = fcurr4;

    /* Process third sample for first tap */
    fnext3 = fcurr3 + ((*pk) * fcurr2);
    gnext3 = (fcurr3 * (*pk)) + fcurr2;

    /* Process fourth sample for first tap */
    fnext4 = fcurr4 + ((*pk) * fcurr3);
    gnext4 = (fcurr4 * (*pk++)) + fcurr3;

    /* Update of f values for next coefficient set processing */
    fcurr1 = fnext1;
    fcurr2 = fnext2;
    fcurr3 = fnext3;
    fcurr4 = fnext4;

    /* Loop unrolling.  Process 4 taps at a time . */
    stageCnt = (numStages - 1u) >> 2u;

    /* Loop over the number of taps.  Unroll by a factor of 4.   
     ** Repeat until we've computed numStages-3 coefficients. */

    /* Process 2nd, 3rd, 4th and 5th taps ... here */
    while(stageCnt > 0u)
    {
      /* Read g1(n-1), g3(n-1) .... from state */
      gcurr1 = *px;

      /* save g1(n) in state buffer */
      *px++ = gnext4;

      /* Process first sample for 2nd, 6th .. tap */
      /* Sample processing for K2, K6.... */
      /* f2(n) = f1(n) +  K2 * g1(n-1) */
      fnext1 = fcurr1 + ((*pk) * gcurr1);
      /* Process second sample for 2nd, 6th .. tap */
      /* for sample 2 processing */
      fnext2 = fcurr2 + ((*pk) * gnext1);
      /* Process third sample for 2nd, 6th .. tap */
      fnext3 = fcurr3 + ((*pk) * gnext2);
      /* Process fourth sample for 2nd, 6th .. tap */
      fnext4 = fcurr4 + ((*pk) * gnext3);

      /* g2(n) = f1(n) * K2  +  g1(n-1) */
      /* Calculation of state values for next stage */
      gnext4 = (fcurr4 * (*pk)) + gnext3;
      gnext3 = (fcurr3 * (*pk)) + gnext2;
      gnext2 = (fcurr2 * (*pk)) + gnext1;
      gnext1 = (fcurr1 * (*pk++)) + gcurr1;


      /* Read g2(n-1), g4(n-1) .... from state */
      gcurr1 = *px;

      /* save g2(n) in state buffer */
      *px++ = gnext4;

      /* Sample processing for K3, K7.... */
      /* Process first sample for 3rd, 7th .. tap */
      /* f3(n) = f2(n) +  K3 * g2(n-1) */
      fcurr1 = fnext1 + ((*pk) * gcurr1);
      /* Process second sample for 3rd, 7th .. tap */
      fcurr2 = fnext2 + ((*pk) * gnext1);
      /* Process third sample for 3rd, 7th .. tap */