Neural Networks

Inspired by neurons and their connections in the brain, neural network is a representation used in machine learning. After running the back-propagation learning algorithm on a given set of examples, the neural network can be used to predict outcomes for any set of input values. Neural Networks...

Similar to using the extended Kalman filter, Neural Networks can also be trained through parameter estimation using the unscented Kalman filter. This file provides a function for this purpose. It also includes an example to show how to use this function. It requires the unscented Kalman filter,...

This set of programs correspond to demos, exercises, and implementations of algorithms described inAbdi H. (1994) Les Reseaux de Neurone (in French) andin (in English)Abdi, Valentin, Edelman (1999) Neural Networks. SageThese include:Linear auto and hetero associators, radial basis function...


Platforms: Matlab

dANN library can help create artificial neural networks within other programs. It is currently written in Java, C++, and C#. However, C++ and C# versions can only be obtained through the SVN at the moment. Also, the C++ and C# versions are not properly documented and cleaned up, although they...


Platforms: *nix

The large classification margin is the most usual approach to achieve good generalization. The most known maximal margin algorithm is SVM, for which different kernels have been investigated. Unfortunately, in the context of some real world problems, such as on-the-fly object detection, the use of...


Platforms: Matlab

Simple tutorial on pattern recognition using back propagation neural networks. the program has 3 classes with 3 images per class.


Platforms: Matlab

Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported.It...


Platforms: BSD Solaris

Tremani Neural Network allows you to build, train and employ neural networks in PHP. It is easy to use and set up, and does not rely on external software to be installed on your webserver. Above all, the software is open source, which means you can use and modify it freely.A neural network can be...


Platforms: Windows, Mac, *nix, PHP, BSD Solaris

Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported.It...


Platforms: BSD Solaris

SFAM is an incremental neural network classifier. It is a simple and fast version of Fuzzy ARTMAP (FAM). Both FAM and SFAM produce the same output given the same input.References:[1] Kasuba, T. (1993). "Simplified fuzzy ARTMAP." AI Expert, Nov., 18d-deOCt25.[2] Carpenter, G. A., Grossberg, S.,...


Platforms: Matlab

This package includes files for modelling nonlinear dynamic systems using a recurrent generalized neural network. The learning scheme uses the complex method of nonlinear nonderivative optimization, thereby avoiding the problems of computing the derivative of an infinite impulse response filter...


Platforms: Matlab

Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.


Platforms: Windows, Mac, Linux

This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.


Platforms: Windows, Mac, Linux

This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot navigation and others (see references for more...


Platforms: Matlab

Character Recognition Using Neural NetworksSteps to use this GUI.1. Open the GUI figure, run it. (accept the matlab to change its directory to new location where the file is stored)2. First we need to teach Character to computer. For this type the Character in the textbox space provided and press...


Platforms: Matlab

Cellular neural networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference that communication is allowed between neighbouring units only.in this system, 'A' template is feedback matrix, and 'B' template is control matrix.also, 'I' is Bias value.all image...


Platforms: Matlab

The extended Kalman filter can not only estimate states of nonlinear dynamic systems from noisy measurements but also can be used to estimate parameters of a nonlinear system. A direct application of parameter estimation is to train artificial neural networks. This function and an embeded example...


Platforms: Matlab

JavaSOM package is an implementation of self-organizing maps (SOM), based on neural networks, to Java2 programming language and utilization of XML based application languages for information exchange and visualization.


Platforms: *nix

SINCO is a GPL library with functions to implement Artificial Neural Networks simulators. You are free to define the network (ilimited neurons and layers) and the functions (training, threshold, etc.).


Platforms: *nix

AI::NNFlex is a base Perl class for implementing neural networks. SYNOPSIS use AI::NNFlex; my $network = AI::NNFlex->new(config parameter=>value); $network->add_layer( nodes=>x, activationfunction=>function); $network->init(); $network->lesion( nodes=>PROBABILITY,...


Platforms: *nix