Character Recognition Using Neural Networks
Steps 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 "TEACH".
3. You can save all the taught data.
4. For retrival, click start.
A neural networks framework for solving problems and processing data using neural networks of various descriptions.
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...
this model show the design of sun seeker control system using neural network model refrence with neural network toolbox and SIMULINK with MATLAB
Calculates Loudness Level according to ISO-226:2003 using Artificial Neural Networks for any SPL.
This function is an update of work of:
VdoTsctor Espinoza, Rodolfo Venegas, Sergio Floody
"Modelo de Sonoridad...
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.
JCortex is a complete solution that allows software developers create, educate and use Artificial Neural Networks in Java projects. Splits in two elements: JCortex Framework, an ANN Java framework; and JCortexBuilder, its graphic development...
Simple tutorial on pattern recognition using back propagation neural networks. the program has 3 classes with 3 images per class.
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.
This project aims at creating a flexible, extendible and re-usable neural network library, and an XML based programming language to create, train and run neural networks using the above mentioned library.
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,...
This set of programs correspond to demos, exercises, and implementations of algorithms described in
Abdi H. (1994) Les Reseaux de Neurone (in French) and
in (in English)
Abdi, Valentin, Edelman (1999) Neural Networks. Sage
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'...
Neural Network Based Control System Design Toolkit Version 2
The NNCTRL toolkit is a set of tools for design and simulation of control systems based on neural networks. The following designs are available:
o Direct inverse...
NeuronDotNet is a neural network engine written in C#. It provides an interface for advanced AI programmers to design various types of artificial neural networks and use them.
SprinN, the best prediction tool based on Artificial Intelligence techniques (Artificial Neural Networks), gives you accurate open, hold and close recommendations for your investments in the Capital Markets. SprinN allows you to select the risk of...
SprinN, Capital Markets Predictions with Neural Networks.SprinN, the best prediction tool based on Artificial Intelligence techniques (Artificial Neural Networks), gives you accurate open, hold and close recommendations for your investments in the...
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. Several nonlinear model structures based on multilayer...
CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.
Broccoli contains:-real and complex numbers,vectors,matrices,functions,polynomials-function minimizers,evolutionary algorithms,neural networks-pdfs,cdfs,max-likelihood,regression,DGPs,PRNGs,armax,garch,statistical estimation etc.-friendly...