代码搜索：Quantization
找到约 3,139 项符合「Quantization」的源代码
代码结果 3,139
www.eeworm.com/read/245941/12770974
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/330850/12864991
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
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/317622/13500895
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat
www.eeworm.com/read/150018/5694548
py range_bec_perf.py
"""
The following script does BEC quantization using regular and
irregular codes of various sizes.
"""
import random
import pycodes
from pycodes.utils import CodeMaker
from pycodes.utils.bec_quant
www.eeworm.com/read/150018/5694559
py range_bec_perf.py
"""
The following script does BEC quantization using regular and
irregular codes of various sizes.
"""
import random
import pycodes
from pycodes.utils import CodeMaker
from pycodes.utils.bec_quant
www.eeworm.com/read/478430/6717754
~pas colorquantizationlibrary.~pas
// Gervautz-Purgathofer Octree Color Quantization Algorithm
// Delphi 3 version of C++ CQuantizer class in Microsoft Systems Journal,
// "Wicked Code" column, October 1997, pp. 79-84, in the "P
www.eeworm.com/read/264745/11303043
m coeffquantizeerr.m
function CoeffQuantizeErr(b,a,maxbits,ftype,f,Fs)
%COEFFICIENT QUANTIZATION ERROR ANALYSIS
n=256;
for nbits=2:maxbits
[B,A]=QuantizeCoeff(b,a,nbits); % quantize all coeffs
[B,A] = sos2tf(
www.eeworm.com/read/405069/11472243
m dslvq.m
function [patterns, targets, w] = DSLVQ(train_patterns, train_targets, Nmu, plot_on)
%Reduce the number of data points using distinction sensitive linear vector quantization
%Inputs:
% train_pat