ann.mdl

一个很好用的自适应人工神经网络模型库

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  Created		  "Tue Jan 16 16:15:32 2007"
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  LastModifiedBy	  "campa"
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  LastModifiedDate	  "Wed May 09 17:01:02 2007"
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      Name		      "ADALINE"
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      MaskType		      "Adaline NN"
      MaskDescription	      "  Self Adaptive Discrete Time MIMO Linear Neura"
"l Network"
      MaskHelp		      "<p>\n  This Neural Network is used to adaptivel"
"y approximate\n  an affine vector field y=W*x+k, with the input vector \n  x "
"being a function of time.\n</p>\n<p>\n  The first input is x. <br>\n  The sec"
"ond input is the error signal (i.e. e=y-ys). <br>\n  The third input is the l"
"earning enable:\n       with LE=1 the learning is enabled, \n       with LE=0"
" the learning is disabled.\n</p>\n<p>\n  The first output is the learned func"
"tion ys(x). <br>\n  The second output is the states matrix reshaped columnwis"
"e. <br>\n</p>\n<p>\n  The first parameter in the mask is a vector containing "
"Ni and No, \n  namely the dimensions (number of elements) of x and y.\n</p>\n"
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"x.\n</p>\n<p>\n  The initial condition could be either a vector of No*(Ni+1) "
"\n  parameters or a scalar. In the latter case, the scalar\n  is repeated No*"
"(Ni+1) times to form the initial condition vector.\n</p>\n<p>\n  OUTPUT EQUAT"
"ION: <br>\n  At any given time t, if x(t) is the input vector, \n  then the h"
"-th output of the neural network is : <br>\n  ys(h,t)=0.1*Wo(h,t)+Ws(h,t)*x(t"
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"d the rest of the h-th row of the state matrix W(t). <br>\n<br>\n  STATE EQUA"
"TION (Learning Algorithm): <br>\n  The state matrix W(t) is updated according"
" to the gradient rule:\n  W(t+T)=W(t)+eta*(dys/dW)*e(t)-eta*gamma*W(t) <br>\n"
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"ath. \n  For further reference see some papers on the ADALINE NN.<br>\n</p>\n"
"<p>\n  Giampiero Campa, June 20 2003\n</p>"
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	  MaskHelp		  "<p>\nElements of input and output matrices "
"are taken columnwise.\n</p>\n<p>\nTo use this block you should have the smxl "
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	  MaskPromptString	  "[n p m]"
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	  MaskDescription	  "  Real Varying Matrices Multiplication\n  I"
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	  MaskHelp		  "<p>\nElements of input and output matrices "
"are taken columnwise.\n</p>\n<p>\nTo use this block you should have the smxl "
"library in your path.\n</p>\n"
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