代码搜索：Buzo
找到约 26 项符合「Buzo」的源代码
代码结果 26
www.eeworm.com/read/430762/8729028
txt vqlbg.txt
function r = vqlbg(d,k)
% VQLBG Vector quantization using the Linde-Buzo-Gray algorithme
%
% Inputs: d contains training data vectors (one per column)
% k is number of centroids required
www.eeworm.com/read/451878/7454741
m vqlbg.m
function r = vqlbg(d,k)
% VQLBG Vector quantization using the Linde-Buzo-Gray algorithme
%
% Inputs: d contains training data vectors (one per column)
% k is number of centroids required
www.eeworm.com/read/326814/13115148
m vqlbg.m
function r = vqlbg(d,k)
% VQLBG Vector quantization using the Linde-Buzo-Gray algorithme
%
% Inputs: d contains training data vectors (one per column)
% k is number of centroids required
%
% Out
www.eeworm.com/read/321469/13404255
m vqlbg.m
function r = vqlbg(d,k)
% VQLBG Vector quantization using the Linde-Buzo-Gray algorithme
%
% Inputs: d contains training data vectors (one per column)
% k is number of centroids required
%
% Out
www.eeworm.com/read/150238/12302611
m vqlbg.m
function r = vqlbg(d,k)
% VQLBG Vector quantization using the Linde-Buzo-Gray algorithme
%
% Inputs: d contains training data vectors (one per column)
% k is number of centroids required
www.eeworm.com/read/372550/9503852
m kmeanlbg.m
function [x,esq,j] = kmeanlbg(d,k)
%KMEANLBG Vector quantisation using the Linde-Buzo-Gray algorithm [X,ESQ,J]=(D,K)
%
%Inputs:
% D contains data vectors (one per row)
% K is number of centres re
www.eeworm.com/read/365161/9876533
m kmeanlbg.m
function [x,esq,j] = kmeanlbg(d,k)
%KMEANLBG Vector quantisation using the Linde-Buzo-Gray algorithm [X,ESQ,J]=(D,K)
%
%Inputs:
% D contains data vectors (one per row)
% K is number of centres re
www.eeworm.com/read/467759/7000697
m kmeanlbg.m
function [x,esq,j] = kmeanlbg(d,k)
%KMEANLBG Vector quantisation using the Linde-Buzo-Gray algorithm [X,ESQ,J]=(D,K)
%
%Inputs:
% D contains data vectors (one per row)
% K is number of centres re
www.eeworm.com/read/236873/7119080
m kmeanlbg.m
function [x,esq,j] = kmeanlbg(d,k)
%KMEANLBG Vector quantisation using the Linde-Buzo-Gray algorithm [X,ESQ,J]=(D,K)
%
%Inputs:
% D contains data vectors (one per row)
% K is number of centres re
www.eeworm.com/read/458010/7314214
m kmeanlbg.m
function [x,esq,j] = kmeanlbg(d,k)
%KMEANLBG Vector quantisation using the Linde-Buzo-Gray algorithm [X,ESQ,J]=(D,K)
%
%Inputs:
% D contains data vectors (one per row)
% K is number of centres re