代码搜索：patterns
找到约 8,017 项符合「patterns」的源代码
代码结果 8,017
www.eeworm.com/read/289641/7104599
m antparset.m
function antpar=antparset(varargin)
%ANTPARSET Antenna parameter configuration for WIMi
% ANTPAR=ANTPARSET sets default parameters for the input struct ANTPAR.
%
% Default parameters are [
www.eeworm.com/read/289641/7104605
m wim_core.m
%WIM_CORE Channel coefficient computation for a geometric channel model
% [H DELTA_T FINAL_PHASES FINAL_PHASES_LOS]=WIM_CORE(WIMPAR,LINKPAR,ANTPAR,BULKPAR,BSGAIN,BSGAIN_LOS,MSGAIN,MSGAIN_LOS,OFFSET
www.eeworm.com/read/456112/7357507
htm related-1.htm
Related Books
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www.eeworm.com/read/456112/7357700
htm disc4-1.htm
Discussion fo Structural Patterns
function setFocus() {
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} else
www.eeworm.com/read/456112/7358461
htm related.htm
Related Books
/* This is needed because the windows in not part of a frame. */
if(top._appletFrame != null && top._appletFrame._loaded)
www.eeworm.com/read/448315/7535284
m antparset.m
function antpar=antparset(varargin)
%ANTPARSET Antenna parameter configuration for SCM
% ANTPAR=ANTPARSET sets default parameters for the input struct ANTPAR.
%
% Default parameters are [ {
www.eeworm.com/read/440460/7689024
m plotbppats.m
function PlotBpPats(P,D)
% PLOTPATS Plots the training patterns defined by Patterns and Desired.
%
% P - MxN matrix with N patterns of length M.
% The first two values in each pattern a
www.eeworm.com/read/439801/7701597
m antparset.m
function antpar=antparset(varargin)
%ANTPARSET Antenna parameter configuration for SCM
% ANTPAR=ANTPARSET sets default parameters for the input struct ANTPAR.
%
% Default parameters are [ {
www.eeworm.com/read/399996/7816606
m classification_error.m
function [classify, err] = classification_error(D, patterns, targets, region)
%Find a classification error for a given decision surface D and a given set of
%patterns (2xL) and targets (1xL)
%The
www.eeworm.com/read/397099/8068743
m classification_error.m
function [classify, err] = classification_error(D, patterns, targets, region)
%Find a classification error for a given decision surface D and a given set of
%patterns (2xL) and targets (1xL)
%The