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Algorithm 的代码
algorithm.html,v
head 1.1;
access;
symbols;
locks; strict;
comment @# @;
1.1
date 2005.06.05.06.30.31; author picone; state Exp;
branches;
next ;
desc
@updated links for the new CAVS web site.
@
1.1
log
@temp.te
algorithm.html,v
head 1.1;
access;
symbols;
locks; strict;
comment @# @;
1.1
date 2005.06.05.06.30.31; author picone; state Exp;
branches;
next ;
desc
@updated links for the new CAVS web site.
@
1.1
log
@temp.te
algorithm.java,v
head 1.9;
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locks; strict;
comment @# @;
1.9
date 2005.06.10.19.37.57; author rirwin; state Exp;
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next 1.8;
1.8
date 2005.06.10.15.05.44; author rirwin; state Exp;
branches;
capon_algorithm.m
clc;
clear all;
% 模拟信号
N=12; % 阵源数（可变）
K=200; % 采样点数
M=2; % 第一个为期望信号，第二个为干扰信号
theta=[30,60];
Xt=zeros(N,K);
SNR=0; % 信噪比（可变）
SIR=-20; % 信干比（可变）
Pd=1; % 发射信号功率设为1
Pn=Pd/(10^(SNR/
genetic_algorithm.m
function D = Genetic_Algorithm(train_features, train_targets, params, region);
% Classify using a basic genetic algorithm
% Inputs:
% features - Train features
% targets - Train targets
% Para
rmf_algorithm.m
%检验收匹配滤波器算法的正确性；
clc;
clear;
h=[12 -8 45 -6 23 49];
x=[32 9 -13 -27 10 -3];
whole_sum=sum(h.*x);
for i=1:length(h)
if h(i)
genetic_algorithm.m
function D = Genetic_Algorithm(train_features, train_targets, params, region);
% Classify using a basic genetic algorithm
% Inputs:
% features - Train features
% targets - Train targets
% Para
goertzel_algorithm.c
/*****************************************************************************/
/* */
/* FILENAME