neural network

Kohonen in java

The following java project contains the java source code and java examples used for kohonen. This code is a homework for my University. It uses AI concepts to simulate a Kohonen Neural Network. Enjoy it and don't forgert to vote.

Contains a number of m-files for training and evaluation of the random neural network in matlab

The following Matlab project contains the source code and Matlab examples used for contains a number of m-files for training and evaluation of the random neural network . The RNNSIM v.2 package contains a number of m-files for training and evaluation of the random neural network. It is a more robust version of RNNSIM ver. 1.0 package without a graphical user interface.

The nnsysid toolbox contains a number of tools for identification of nonlinear dynamic systems with in matlab

The following Matlab project contains the source code and Matlab examples used for the nnsysid toolbox contains a number of tools for identification of nonlinear dynamic systems with . Neural Network Based System Identification Toolbox Version 2 The NNSYSID toolbox contains a number of tools for identification of nonlinear dynamic systems with neural networks.

Function approximation using neural network without using toolbox in matlab

The following Matlab project contains the source code and Matlab examples used for function approximation using neural network without using toolbox. This code implements the basic back propagation of error learning algorithm. the network has tanh hidden neurons and a linear output neuron, and applied for predicting y=sin(2pix1)*sin(2pix2). We didn't use any feature of neural network toolbox.

Multilayer perceptron neural network model and backpropagation algorithm for simulink

The following Matlab project contains the source code and Matlab examples used for multilayer perceptron neural network model and backpropagation algorithm for simulink. Multilayer Perceptron Neural Network Model and Backpropagation Algorithm for Simulink. Marcelo Augusto Costa Fernandes DCA - CT - UFRN mfernandes@dca.ufrn.br

Neural Network Matlab Code

Artificial neural networks (ANNs) are computational models inspired by an animal's central nervous systems (in particular the brain) which is capable of machine learning as well as pattern recognition. Artificial neural networks are generally presented as systems of interconnected "neurons" which can compute values from inputs.

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