< Master index Index for ./freetb4matlab/nnet >

Index for ./freetb4matlab/nnet

Matlab files in this directory:

 dhardlim%
 dividerand% Divide the vectors in training, validation and test group according to
 dposlin% @code{poslin} is a positive linear transfer function used
 dsatlin%
 dsatlins% A neural feed-forward network will be trained with @code{trainlm}
 hardlim%
 hardlims%
 ind2vec% @code{vec2ind} convert indices to vector
 isposint% @code{isposint} returns true for positive integer values.
 logsig% @code{logsig} is a non-linear transfer function used to train
 mapstd% Map values to mean 0 and standard derivation to 1.
 min_max% @code{min_max} returns variable Pr with range of matrix rows
 newff% @code{newff} create a feed-forward backpropagation network
 newp% @code{newp} create a perceptron
 poslin% @code{poslin} is a positive linear transfer function used
 poststd% @code{poststd} postprocesses the data which has been preprocessed by @code{prestd}.
 prestd% @code{prestd} preprocesses the data so that the mean is 0 and the standard deviation is 1.
 purelin% @code{purelin} is a linear transfer function used
 satlin% A neural feed-forward network will be trained with @code{trainlm}
 satlins% A neural feed-forward network will be trained with @code{trainlm}
 saveMLPStruct% @code{saveStruct} saves a neural network structure to *.txt files
 sim% @code{sim} is usuable to simulate a before defined neural network.
 subset% @code{subset} splits the main data matrix which contains inputs and targets into 2 or 3 subsets
 tansig% @code{tansig} is a non-linear transfer function used to train
 train% A neural feed-forward network will be trained with @code{train}
 trastd% @code{trastd} preprocess additional data for neural network simulation.
 vec2ind% @code{vec2ind} convert vectors to indices

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