代码搜索：Algorithm
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www.eeworm.com/read/287119/8720124
h kgsha.h
/*******************************************************************
*
* Copyright (c) 1994-1999 Jetico, Inc., Finland
* All rights reserved.
*
* File: kgsha.h
* Revision: $Id: kgsha.h,v 1.2 20
www.eeworm.com/read/430527/8740458
m d_nlpow.m
%D_NLPOW HOSA Demo: Identification of Second-Order Volterra Systems
% Powers' algorithm, for arbitrary inputs
%
echo off
% A. Swami Oct 18, 1997.
% Copyright (c) 19
www.eeworm.com/read/430527/8740703
m contents.m
% Higher-Order Spectral Analysis Toolbox.
% Version 2.0.3 (R12 compliant) 27 Dec 2000
%
% New Features.
% Readme - Important release information about the HOSA Toolbox
%
www.eeworm.com/read/286662/8751810
m contents.m
% HMM's
% HMM_Backward - HMM backward algorithm
% HMM_Boltzmann - Find the transition matrices of an HMM using Boltzmann networks
% HMM_Decoding - Find probable states fro
www.eeworm.com/read/429878/8784241
htm rbftrain.htm
Netlab Reference Manual rbftrain
rbftrain
Purpose
Two stage training of RBF network.
Description
net = rbftrain
www.eeworm.com/read/429797/8788427
m func_threshold.m
function thre = func_threshold(I)
% Compute an optimal threshold for seperating the data into two classes [1].
% This algorithm can be summarized as follows. The histogram is initially segmented
www.eeworm.com/read/285876/8803447
m contents.m
% Higher-Order Spectral Analysis Toolbox.
% Version 2.0.3 (R12 compliant) 27 Dec 2000
%
% New Features.
% Readme - Important release information about the HOSA Toolbox
%
www.eeworm.com/read/428849/8834402
pl references.pl
{
"Anderson62" =>"T.W.Anderson and R.R.Bahadur. Classification into two
multivariate normal distributions with differrentia covariance matrices.
Anals of Mathematical Statistics, 33:420--431, Ju
www.eeworm.com/read/428479/8865425
txt readme.txt
========================================================================
MICROSOFT FOUNDATION CLASS LIBRARY : NBC_Algorithm
===================================================================
www.eeworm.com/read/427233/8959579
m mf.m
%MF.m
%This program solves the maximum flow problem by using Dinic algorithm.
n=input('Enter the vertices number of the graph:n= ')
C=input('Enter the capacity adjacent matrix of the graph:[C(1,