Artificial neural networks

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.

Feedback linearizing control using hybrid neural networks identified by sensitivity approach in matlab

The following Matlab project contains the source code and Matlab examples used for feedback linearizing control using hybrid neural networks identified by sensitivity approach. Globally Linearizing Control (GLC) is a control algorithm capable of using non-linear process model directly.

Simple perceptron in matlab

The following Matlab project contains the source code and Matlab examples used for simple perceptron. Perceptron is an algorithm for supervised classification of an input into one of several possible non-binary outputs. This mfile is a simple type of perceptron to who like to learn about the perceptron type of artificial neural networks

The matrix implementation of the two layer multilayer perceptron (mlp) neural networks. in matlab

The following Matlab project contains the source code and Matlab examples used for the matrix implementation of the two layer multilayer perceptron (mlp) neural networks.. The matrix implementation of the MLP and Backpropagation algorithm for two-layer Multilayer Perceptron (MLP) neural networks. Marcelo Augusto Costa Fernandes DCA - CT - UFRN mfernandes@dca.ufrn.br

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

The radial basis function (rbf) with lms algorithm for simulink

The following Matlab project contains the source code and Matlab examples used for the radial basis function (rbf) with lms algorithm for simulink. The Radial Basis Function (RBF) Batch-mode training Fixed centers selected at random The Gaussian basis functions Computing the output weights with LMS algorithm Marcelo Augusto Costa Fernandes DCA - CT - UFRN mfernandes@dca.ufrn.br

Radial basis function with k mean clustering in matlab

The following Matlab project contains the source code and Matlab examples used for radial basis function with k mean clustering. The program is the implementation of Radial Basis Function for classification task Using K-Mean Clustering Two example are given check one at a time Solution of K*W=T using Pseudo Inverse technique Multiply K' on Both sides to get K'*K*W=K'*T Multiply with the inverse of (K'*K) on Both sides to get W=inv(K'*K)*K'*T .

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.

Neural network simple programs for beginners in matlab

The following Matlab project contains the source code and Matlab examples used for neural network simple programs for beginners . The tutorial contains programs for PERCEPTRON and LINEAR NETWORKS  Classification with a 2-input perceptron  Classification with a 3-input perceptron  Classification with a 2-neuron perceptron  Classification with a 2-layer perceptron Pattern association with a linear neuron  Training a linear layer  Adaptive linear layer  Linear prediction  Adaptive linear prediction .

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