代码搜索:Approach

找到约 1,300 项符合「Approach」的源代码

代码结果 1,300
www.eeworm.com/read/247726/12623536

m fpica.m

function [A, W] = fpica(X, whiteningMatrix, dewhiteningMatrix, approach, ... numOfIC, g, finetune, a1, a2, myy, stabilization, ... epsilon, maxNumIterations, maxFinetune, initState, ... guess
www.eeworm.com/read/235187/14082443

m unidecor.m

function [H, Qaj] = unidecor(example) %UNIDECOR Computes a decorrelating transformation as described in % Liu et al. (1999) A new approach to GPS ambiguity % decorrelation, Jou
www.eeworm.com/read/132535/14085714

m fpica.m

function [A, W] = fpica(X, whiteningMatrix, dewhiteningMatrix, approach, ... numOfIC, g, finetune, a1, a2, myy, stabilization, ... epsilon, maxNumIterations, maxFinetune, initState, ... guess
www.eeworm.com/read/111805/15503019

java lottery.java

// Chapter 17 Exercise 7 /* We have a different approach for the selection button tooltips and the tooltips for the control buttons. For the former, we use the setToolTipText() method inherited
www.eeworm.com/read/106648/15631433

m fpica.m

function [A, W] = fpica(X, whiteningMatrix, dewhiteningMatrix, approach, ... numOfIC, g, finetune, a1, a2, myy, stabilization, ... epsilon, maxNumIterations, maxFinetune, initState, ... guess
www.eeworm.com/read/182116/9216904

security

SECURITY - why zgv is setuid root, etc. --------------------------------------- This file is an attempt to explain the approach zgv takes to security. I know setuid binaries are scary things, but zgv
www.eeworm.com/read/374472/9404032

readme

This package contains software to find the threshold of an LDPC code in a Gaussian channel using the Fast Enough Evolution of Densities (FEED) algorithm. FEED is based on the approach of Jin and Ri
www.eeworm.com/read/273787/10901263

m efilter.m

% H = EFILTER(ALFA, STOPEDGE, PASSEDGE, ORDER) % % This program is to realize the Lowpass filter Algorithm of the paper % 'Eigenfilters: A New Approach to Least-Squares FIR Filter Design and % Ap
www.eeworm.com/read/448535/7531363

m hmmnorm.m

function d = hmmnorm(branchweight,y,state,nextstate) % % Compute the branch norm for the HMM using the Viterbi approach % % function d = hmmnorm(branchweight,y,state,nextstate) % % branchweight
www.eeworm.com/read/199981/7813814

m lda.m

function [eigvector, eigvalue, Y] = LDA(X,gnd) % LDA: Linear discriminant analysis (Fisherfaces approach PCA+LDA) % % [eigvector, eigvalue] = LDA(X, gnd) % % Input: %