Neural Network Simulator

Adaptive Resonance Theory (ART) Neural Network art1.zip contains: art1s.m - M-file for simulation of ART1 NN letno.m - M-file for generating input binary patterns (letters A-Z) for use with art1s.m noisy.m - M-file which introduces noise in the patterns. Used by letno.m letplot.m - M-file for... Platforms: Matlab

This demo shows some examples for image pre-processing before the recognition stage. the first example is just some commnads of image processing which are commonly used for preprocessing, while the second example shows how to use the simple command to automate the image processing stage... Platforms: Matlab

The function nntest6.m is a Neural Network viewer and controller that allows experimentation with a feed-forward Neural Network. Features: Platforms: Matlab

Encog is an advanced neural network and bot programming library. Encog can be used independently either to create neural networks or HTTP bot programs. Encog also includes classes that combine these two advanced features. Encog contains classes for Feedforward Neural Networks, Hopfield Neural... Platforms: Mac

Verax SNMP agent simulator is a tool that can simulate multiple SNMPv1/v2c agents on a single host on standard 161 port through multi-netting. It allows IT personnel to build virtual, simulated networks of devices without purchasing any additional hardware, for instance for testing purposes.... Platforms: Windows, *nix, Java

The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover Platforms: Windows, Mac, Linux

TDL - Win Neural Net Pattern Recog. Tool Quick, hassle-free automatic construction of NN by use of evolutionary processes. Trans-Dimensional Learning allows multiple data sets to be learned incrementally, regardless of differences in number of inputs and outputs. Complete graphical support of... Platforms: Windows

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

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

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

Source code for fast training of multilayer perceptron for approximation. Example training and validation data files included. Source code for applying the trained network. Resulting networks can be pruned by NuMap7.06. The training algorithm can be modified to be substantially better than BP. A... Platforms: Windows

Source code for fast training of multilayer perceptron classifier. Example training and validation data files included. Source code for applying the trained network. Resulting networks can be pruned by NuClass7.06. The training algorithm can be modified to be substantially better than BP. A... Platforms: Windows

These files support the webinar titled "Developing Models from Experimental Data Using System Identification Toolbox". The webinar was presented on April 05, 2007 and can be found at:http://www.mathworks.com/wbnr30317For other webinars and demos related to System Identification Toolbox, please... Platforms: Matlab

The Kalman filter is actually a feedback approach to minimize the estimation error in terms of sum of square. This approach can be applied to general nonlinear optimization. This function shows a way using the extended Kalman filter to solve some unconstrained nonlinear optimization problems. Two... Platforms: Matlab

The Kalman filter can be interpreted as a feedback approach to minimize the least equare error. It can be applied to solve a nonlinear least square optimization problem. This function provides a way using the unscented Kalman filter to solve nonlinear least square optimization problems. Three... 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

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. Platforms: Matlab

NeurAnim is a research aid for computational neuroscience. It is used to visualise and animate neural network simulations in 3D, and to render movies of these animations for use in presentations. Platforms: *nix