代码搜索：initialisation
找到约 2,024 项符合「initialisation」的源代码
代码结果 2,024
www.eeworm.com/read/491155/6441100
m gr.m
function [sys,x0,str,ts]=zon(t,x,u,flag)
%dispath the flag.the switch function controls the calls to
%s_function routines at each simulation stage.
switch flag;
case 0
sizes =simsizes;
%Lo
www.eeworm.com/read/342008/12047500
m emclust.m
%EMCLUST Expectation - Maximization clustering
%
% [D,V] = emclust(A,W,n)
%
% The untrained classifier W is used to update an initially labelled
% dataset A by the following two steps:
% 1. train W by
www.eeworm.com/read/293183/8310811
m emclust.m
%EMCLUST Expectation - Maximization clustering
%
% [D,V] = emclust(A,W,n)
%
% The untrained classifier W is used to update an initially labelled
% dataset A by the following two steps:
% 1. train W by
www.eeworm.com/read/431675/8661809
m bpxnc.m
%BPXNC Neural net classifier based on MATHWORK's trainbpx
%
% [W,R] = bpxnc(A,n,iter,Win,T,fid)
%
% A feedforward neural network classifier with length(n) hidden
% layers having n(i) neurons in la
www.eeworm.com/read/431675/8662086
m lmnc.m
%LMNC Levenberg-Marquardt neural net classifier
%
% [W,R] = lmnc(A,n,iter,Win,T,fid)
%
% A feedforward neural network classifier with length(n) hidden
% layer with n(i) units is computed for the d
www.eeworm.com/read/160546/10519884
ini system.ini
;--------------------------------------------
; Experiment Platform of Information Security - System.ini
;
; Initialisation file
;
; $Header: /XXSystem/Profiles/System.ini 3/10/06 15:37 Jackie
www.eeworm.com/read/418695/10935231
m bpxnc.m
%BPXNC Neural net classifier based on MATHWORK's trainbpx
%
% [W,R] = bpxnc(A,n,iter,Win,T,fid)
%
% A feedforward neural network classifier with length(n) hidden
% layers having n(i) neurons in la
www.eeworm.com/read/418695/10935435
m lmnc.m
%LMNC Levenberg-Marquardt neural net classifier
%
% [W,R] = lmnc(A,n,iter,Win,T,fid)
%
% A feedforward neural network classifier with length(n) hidden
% layer with n(i) units is computed for the d
www.eeworm.com/read/462044/7211673
m doublement.m
function res = doublement(u0,n)
u = zeros(n,1); %initialisation du tableau avec des zeros
u(1)=u0; %initialisation de la recurrence
for k=1:n-1; %recurrence
u(k+1)=2*u(k)^2-1;
end
res=u
www.eeworm.com/read/459685/7268785
bshrc beanshellassertion.bshrc
// Sample BeanShell Assertion initialisation file
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with