csub.m

FS1016源代码

% MATLAB SIMULATION OF NSA FS-1016 CELP v3.2
% COPYRIGHT (C) 1995-99 ANDREAS SPANIAS AND TED PAINTER
%
% This Copyright applies only to this particular MATLAB implementation
% of the FS-1016 CELP coder.  The MATLAB software is intended only for educational
% purposes.  No other use is intended or authorized.  This is not a public
% domain program and distribution to individuals or networks is strictly
% prohibited.  Be aware that use of the standard in any form is goverened
% by rules of the US DoD.  Therefore patents and royalties may apply to
% authors, companies, or committees associated with this standard, FS-1016.  For
% questions regarding the MATLAB implementation please contact Andreas
% Spanias at [phone].  For questions on rules,
% royalties, or patents associated with the standard, please contact the DoD.
%
% ALL DERIVATIVE WORKS MUST INCLUDE THIS COPYRIGHT NOTICE.
%
% ******************************************************************
% CSUB
%
% MATLAB REVISION HISTORY
%
% PORTED TO MATLAB FROM CELP 3.2a C RELEASE
% 6-20-94
%
% ******************************************************************
%
% DESCRIPTION
%
% Run adaptive and stochastic codebook searches
%
% DESIGN NOTES
%
% See individual subroutines
%
% VARIABLES
%
% INPUTS
%   s          -     Speech or residual segment
%   l          -     Stochastic analysis frame size
%   lp         -     Adaptive (pitch) analysis frame size
%
% OUTPUTS
%   v          -     Optimum excitation vector
%
% INTERNALS
%
% GLOBALS
%   e0         -     Codebook search initial error and updated error
%   d1a        -     Memory 1/P(z)       (pitch)
%   d1b        -     Memory 1/P(z)       (pitch)
%   d2a        -     Memory 1/A(z)       (spectrum)
%   d2b        -     Memory 1/A(z)       (spectrum)
%   d3a        -     Memory A(z)         (spectrum)
%   d3b        -     Memory A(z)         (spectrum)
%   d4a        -     Memory 1/A(z/gamma) (spectrum)
%   d4b        -     Memory 1/A(z/gamma) (spectrum)
%   mxsw       -     Modified excitation control switch
%   nseg       -     Segment (subframe) counter, cumulative
%
% CONSTANTS
%   MAXNO      -     Predictor order
%   MAXPA      -     Dimension of d1a, d1b
%
% ******************************************************************

function v = csub( s, l, lp )

% DECLARE GLOBAL CONSTANTS
global MAXNO MAXPA;

% DECLARE GLOBAL VARAIBLES
global e0 d1a d1b d2a d2b d3a d3b d4a d4b mxsw nseg;

% INITIALIZE LOCAL AND STATIC VARIABLES
e0 = zeros( l, 1 );

% FIND INITIAL ERROR WITHOUT PITCH VQ
[ d1a, d2a, d3a, d4a ] = confg( s, l, d1a, d2a, d3a, d4a, 0, 1, 1, 1 );

% RESTORE FILTER MEMORIES: 1/A(Z), A(Z), 1/A(Z/GAMMA)
d2a = d2b;
d3a = d3b;
d4a = d4b;

% FIND IMPULSE RESPONSE OF THE PERCEPTUAL WEIGHTING FILTER, h(n)
impulse(l);

% COMPUTE EUCLIDEAN NORM OF THE FIRST ERROR SIGNAL
if mxsw == 1
    mexcite1( l );
end

% DO PITCH (ADAPTIVE) CODEBOOK SEARCH
% GET PP PARAMETERS EVERY SEGMENT IF LP == L, OTHERWISE GET PP
% PARAMETERS ON ODD SEGMENTS
if lp == l
    psearch( l );
elseif rem( nseg, 2 ) == 1
    psearch( lp );
end

% FIND INITIAL ERROR WITH PITCH VQ
e0 = zeros( l, 1 );
[ d1a, d2a, d3a, d4a ] = confg( s, l, d1a, d2a, d3a, d4a, 1, 1, 1, 1 );

% COMPUTE NORM OF SECOND ERROR SIGNAL
if mxsw == 1
    mexcite2( l );
end

% STOCHASTIC CODEBOOK SEARCH
v = cbsearch( l, 0 );

% UPDATE FILTER STATES
e0 = v;
[ d1b, d2b, d3b, d4b ] = confg( s, l, d1b, d2b, d3b, d4b, 1, 1, 1, 1 );
d1a = d1b;
d2a = d2b;
d3a = d3b;
d4a = d4b;