fft_small_model.m

来自「FFT 32k use VHDL MATLAB」· M 代码 · 共 40 行

% function [y, exp_out] = fft_small_model(x,N,INVERSE)         
%                                                                                             
%   calculates the complex block-floating point FFT/IFFT of length N of a                     
%   complex input vector x                                                                    
%                                                                                             
%   Inputs:   x          : Input complex vector of length B*N, where B is                     
%                          the number of blocks over which the length-N FFT is to             
%                          be applied. If the length of the vector is not                     
%                          an integral multiple of N, zeros are                               
%                          appended to the input sequence appropriately.                      
%             N          : Transform Length                                                   
%             INVERSE    : FFT direction                                                      
%                          0 => FFT                                                           
%                          1 => IFFT                                                          
%                                                                                             
%   Outputs   y          : The transform-domain complex vector output                         
%             exp_out    : Block exponent value                                               
%                                                                                             
%   Copyright (C) 1988-2004 Altera Corporation                                                
function [y, exp_out] = fft_small(x,N,INVERSE)         
addpath 'C:/software/altera/MegaCore/fft-v2.1.3/lib//ip_toolbench/../';
% Parameterization Space    
THROUGHPUT=4;
ARCH=0;
DATA_PREC=16;
TWIDDLE_PREC=16;
input_vector_length = length(x);                                                              
number_of_blocks = ceil(input_vector_length/N);                                               
% Zero-stuff last block if necessary                                                          
x = [x, zeros(1,number_of_blocks * N - input_vector_length)];                                 
y=[];                                                                                         
exp_out=[];                                                                                   
for i=1:number_of_blocks                                                                      
    rin = real(x((i-1)*N + 1: i*N));                                                          
    iin = imag(x((i-1)*N + 1: i*N));                                                          
    [roc,ioc,eoc] = sfftmodel(rin,iin,N,THROUGHPUT,ARCH,DATA_PREC,TWIDDLE_PREC,INVERSE);      
    y = [y, roc+j*ioc];                                                                       
    exp_out = [exp_out, eoc];                                                                 
end