Neural Network Example

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.

-Compatible with pre-2010 vers. of Matlab and Neural network toolbox-Trains a perceptron for the spring and one for the damper. -Runs a simulation with forcing function and noise.-If you don't have the toolbox, you can still use my back-propagation.

annie stands for Artificial Neural Network Library and is a C++ API (library) for neural network training and execution. ersions exist for both Windows and flavours of Unix (tested on Linux). The library currently has support for training, saving and executing multi-layer perceptron,...


Platforms: *nix

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

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

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

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

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 little package contains a Parzen Neural Network classifier that can classify data between N classes in D dimensions. The classifier is really fast and simple to learn. The good classification performance can be obtained for a certain class of data distributions. Other classifiers must be...


Platforms: Matlab

This Program allows a Neural Network in conjuction with Image Processing to compute the best picture quality. This is done by splitting the Image into Its RGB components.


Platforms: Matlab

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,...


Platforms: Matlab

Neural Mesh is a purely PHP, fast, easy Neural Network Manager, Administrator and Framework.The highlight of the project is that it allows you to integrate Artificial Intelligence into your applications, quickly and easily, no matter what your experience.


Platforms: PHP

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

A simple Bayesian Network example for exact probabilistic inference using Pearl's message-passing algorithm on singly connected graphs.


Platforms: Matlab

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


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 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

An artificial neural network, currently specialized to save a specific bit pattern, mainly by changing the signal propagation delays in links. More features, variables and algorithms will be added in time.


Platforms: Windows, Mac, Linux

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