Neural

Open source, fast and simple neural processing MATLAB scripts, functions and algorithms. File IO, spike detection, signal processing, seizure detection, closed loop. Functions are compatible with Blackrock Microsystems NEV and NSx files. 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

SNARLI (Simple Neural ARchitecture LIbrary) is a Java package containing a back-prop layer class and classes for the Self-Organizing Map and Incremental Growing Grid. The back-prop class supports sigma-pi connections and back-prop-through-time. Platforms: Windows, Mac, Linux

Given a neural network object, this function returns the closed, symbolic, expression implemented by the network (as a string).This allows you to use a neural network model without relying on the neural network toolbox.Note I only implemented for feed forward nets (MLPs) and not all possible... Platforms: Matlab

This add-in to the PSO Research toolbox (Evers 2009) aims to allow an artificial neural network (ANN or simply NN) to be trained using the Particle Swarm Optimization (PSO) technique (Kennedy, Eberhart et al. 2001).This add-in acts like a bridge or interface between MATLABd-deOaos NN toolbox and... Platforms: Matlab

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

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. Platforms: Matlab

The attached zip file contains what is needed to implement a two layer neural network. This will hopefully be the first part of a broader collection of neural network tools.It can be used to train and simulate a NN with two layers, an input layer and an output layer. The output layer's activation... Platforms: Matlab

-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. 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

This is a learning model for matrix-based data. It can be more efficient than standard vector-based models when the training sample is small or the inputs are matrices, since this model has less parameters than standard ones and exploits an inner structure of the inputs. This model can be... Platforms: Matlab

We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are... Platforms: Matlab

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

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

v(1.0) fSC-Net - Win Neural Net Fuzzy Pattern Recognition. Quick, hassle-free automatic construction of Neural Networks. Incremental learning. Support of fuzzy logic. Hybrid symbolicconnectionist representation. Complete graphical support of training and testing. Point and click recall of network... Platforms: Windows

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

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

AI::NNFlex::Backprop project is a fast, pure perl backprop Neural Net simulator. SYNOPSIS use AI::NNFlex::Backprop; my $network = AI::NNFlex::Backprop->new(config parameter=>value); $network->add_layer(nodes=>x,activationfunction=>function); $network->init(); use... Platforms: *nix