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h netif.h

/* * Copyright (c) 2001-2003 Swedish Institute of Computer Science. * All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, * are permi
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m contents.m

% MININNET % Functions for Neural Network Design demonstrations. % (Do not use if Neural Network Toolbox is available.) % % Transfer functions % compet - Competitive transfer function. % h
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plg serialcomm.plg

Build Log --------------------Configuration: SerialComm - Win32 Debug-------------------- Command Lines Creating temporary file "C:\DOCUME~1\AD
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m test2.m

% DEMONSTRATION PROGRAM FOR TESTING NNARX % % Programmed by Magnus Norgaard, IAU/IMM/EI, Technical Univ. of Denmark % LastEditDate: Aug 21, 1995 close all StopDemo=0; figure guihand=gcf; for
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m test3.m

% DEMONSTRATION PROGRAM FOR TESTING NNARMAX2 % % Programmed by Magnus Norgaard, IAU/IMM/EI, Technical Univ. of Denmark % LastEditDate: Aug 21, 1995 close all StopDemo=0; figure guihand=gcf;
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m elman_app.m

%Elman Application % clf figure(gcf) setfsize(500,500); echo on % MEWELM —— 建立一个Elman神经网络 % TRAIN —— 训练一个神经网络 % SIM —— 对一个神经网络进行仿真 pause %Strik any key to creat a network clc P1=sin(1:
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def h323.def

LIBRARY IIIH323Parser DESCRIPTION "III Network Monitor H.323 Parser DLL. VERSION 2.0 EXPORTS ParserAutoInstallInfo
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htm ch3gla.htm

WEEK 3 -- At a Glance
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m mdnpak.m

function w = mdnpak(net) %MDNPAK Combines weights and biases into one weights vector. % % Description % W = MDNPAK(NET) takes a mixture density network data structure NET % and combines the network w
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m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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