Neural

AI::NeuralNet::Simple is a simple learning module for building neural nets. SYNOPSIS use AI::NeuralNet::Simple; my $net = AI::NeuralNet::Simple->new(2,1,2); # teach it logical or for (1 .. 10000) { $net->train([1,1],[0,1]); $net->train([1,0],[0,1]); $net->train([0,1],[0,1]);... Platforms: *nix

The SigmaPi Neural Network Simulator is designed for time-series processing and neural network research on Unix/X11. Since version 0.5, it uses the LSTM neuron model, the RTRL training algorithm and a heuristic learning rate adaptation based on local update sign-changes. It is GPL-covered, so you... Platforms: *nix

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

AI::NeuralNet::BackProp is a simple back-prop neural net that uses Deltas and Hebbs rule. SYNOPSIS use AI::NeuralNet::BackProp; # Create a new network with 1 layer, 5 inputs, and 5 outputs. my $net = new AI::NeuralNet::BackProp(1,5,5); # Add a small amount of randomness to the network... Platforms: *nix

KXNeur is a X Neural Switcher front-end for KDE. Its a program like Punto Switcher, but has other functionally and features. Last version can get from svn: svn://xneur.ru:3690/xneur/xneur and svn://xneur.ru:3690/xneur/kxneur PS XNeur homepage ( http://xneur.ru ) on Russian only PPS KXNeur... Platforms: *nix

ffnet is meant to be an easy and fast feed-forward neural network training solution for python.. Platforms: *nix

scnANNlib is a Sentinel Chicken Networks Artificial Neural Network Library. Documentation on what is what can be found in README.files. Currently, the API specification and documentation can only be found in the source of the header files (in lib/), but this will be improved in later releases.... Platforms: *nix

SPICE-MLP (the old name is SpiceNeuro or Neural Network Example - NNE) is a small application of Three-Layer Neural Network (NN) with multi-inputs and outputs, written for students who wanted to learn and develop their own NN applications. The purpose of this program is to get you started... Platforms: Windows, Windows Vista, 7

The purpose of this program is to get you started quickly with Neural Network without having to go through lengthy theory of the Neural Network background. Once you understand these programs you will be able to consult the Neural Network materials on a need basis. Spice-SOM's arm is to introduce... Platforms: Windows, Windows Vista, 7

GINNet, also known as the Graphical Interface for Neural Networks was developed as a decision-making platform written in Java. It has been designed in order to favorize the development and use of neural networks. It was create so that it could make, neural networks, teaching and evaluation easier. Platforms: Windows

Multiple Back-Propagation is an easy to use application specially designed for the training of neural networks with the Back-Propagation and the Multiple Back-Propagation algorithms. Platforms: Windows

AnimatLab is a simple, easy to use application specially designed to combine biomechanical simulation and biologically realistic neural networks. You can build the body of an animal, robot, or other machine and place it in a virtual world where the physics of its interaction with the... Platforms: Windows

DynNet is built as a Java library that contains basic elements that are necessary in order to build neural networks. Neural network classical models are already available (Multi-layer perceptron, Kohonen self-organizing maps, neural gas, growing neural gas, etc.). Platforms: Windows

Cognity is designed as an object-oriented neural network library for the Java programming language. The main goal of the library is to provide an easy-to-use, high level architecture for neural network computations along with reasonable performance. Platforms: Windows

RNNLIB is a recurrent neural network library for sequence learning problems. Applicable to most types of spatiotemporal data, it has proven particularly effective for speech and handwriting recognition. Platforms: Mac

This script uses the IAC (interactive-competition-and-activation) model to analyze a database. Scalyze a dils: - The example is taken from Parallel Distributed Processing, a classic text on neural networks. - The field values represent neurons. - The database rows represent excitory... Platforms: Windows, Mac, *nix, Python, BSD Solaris

Develop a Matlab program to demonstrate a neural network autoassociative memory. Show the importance of using the pseudoinverse in reducing cross correlation matrix errors. Show the performance of the autoassociative memory in noise. The results are contained in the Matlab file assoc_mem_demo.m Platforms: Matlab

A very simple program that trains a neural network with 9 images(3 rectangles, 3 triangles and 3 circles)and then simulates the neural network in way to recognize 3 others images(1 rectangles, 1 triangles and 1 circles). Platforms: Matlab

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

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