# Kohonen in java

The following java project contains the java source code and java examples used for kohonen. This code is a homework for my University. It uses AI concepts to simulate a Kohonen Neural Network. Enjoy it and don't forgert to vote.

The following Matlab project contains the source code and Matlab examples used for tsk forecasting.
The tool implements the Takagi-Sugeno-Kang (TSK) model of a fuzzy neural network with a hybrid learning algorithm.

The following Matlab project contains the source code and Matlab examples used for contains a number of m-files for training and evaluation of the random neural network .
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.

The following Matlab project contains the source code and Matlab examples used for very useful for adjusting images .
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.

The following Matlab project contains the source code and Matlab examples used for the nnsysid toolbox contains a number of tools for identification of nonlinear dynamic systems with .
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.

The following Matlab project contains the source code and Matlab examples used for parzen pnn.
This little package contains a Parzen Neural Network classifier that can classify data between N classes in D dimensions.

The following Matlab project contains the source code and Matlab examples used for sgong color reduction.
This color reduction software is based on a new neural network classifier (SGONG).

The following Matlab project contains the source code and Matlab examples used for machine learning balancing a stack of balls.
A genetic algorithm is used to train a neural network controller to balance a stack of balls by applying a lateral force and a torque to the bottom ball.

The following Matlab project contains the source code and Matlab examples used for 3d ternplot.
This is the 3D update of "GTL jetfuel_ternplot with neural network".

The following Matlab project contains the source code and Matlab examples used for a neural network based dynamic forecasting model for trend impact analysis.
Trend Impact Analysis is a simple forecasting approach, yet powerful, within the Futures Studies paradigm.

The following Matlab project contains the source code and Matlab examples used for unsupervised learning with growing neural gas (gng) neural network.
The Growing Neural Gas (GNG) Neural Network belongs to the class of Topology Representing Networks (TRN's).

The following Matlab project contains the source code and Matlab examples used for elman nn.
Elman neural network used as Identifier

The following Matlab project contains the source code and Matlab examples used for unsupervised learning with dynamic cell structures (dcs) neural network.
The Dynamic Cell Structure (DCS-GCS) ANN belongs to the class of Topology Representing Networks (TRN's).

The following matlab project contains the source code and matlab examples used for linear predictive coding.

The following matlab project contains the source code and matlab examples used for wavelet neural network.

The following Matlab project contains the source code and Matlab examples used for adaptive neural networks .
The adaptive Neural Network Library (Matlab 5.

The following matlab project contains the source code and matlab examples used for artificial neural network.

The following matlab project contains the source code and matlab examples used for backpropagation.

The following Matlab project contains the source code and Matlab examples used for function approximation using neural network without using toolbox.
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.

The following Matlab project contains the source code and Matlab examples used for multilayer perceptron neural network model and backpropagation algorithm for simulink.
Multilayer Perceptron Neural Network Model and Backpropagation Algorithm for Simulink.
Marcelo Augusto Costa Fernandes
DCA - CT - UFRN
mfernandes@dca.ufrn.br

The following Matlab project contains the source code and Matlab examples used for mycnn is a matlab implementation of convolutional neural network (cnn). .
The first CNN appeared in the work of Fukushima in 1980 and was called Neocognitron.

Artificial neural networks (ANNs) are computational models inspired by an animal's central nervous systems (in particular the brain) which is capable of machine learning as well as pattern recognition. Artificial neural networks are generally presented as systems of interconnected "neurons" which can compute values from inputs.

The following Matlab project contains the source code and Matlab examples used for jordan recurrent neural network for data classification algorithm.
This is MATLAB Script for Jordan RNN in MATLAB compatible for NNT 5.

The following Matlab project contains the source code and Matlab examples used for fast multilayer feedforward neural network training.
This codes optimizes a multilayer feedforward neural network using first-order stochastic gradient descent. It output the network as a structure, which can then be tested on new data.

The following Matlab project contains the source code and Matlab examples used for a very simple and intuitive neural network implementation.
Short code and easy to understand. Example data set provided.

The following Matlab project contains the source code and Matlab examples used for recurrent fuzzy neural network (rfnn) library for simulink.
This is a collection of four different S-function implementations of the recurrent fuzzy neural network (RFNN) described in detail in [1].

The following Matlab project contains the source code and Matlab examples used for neural network training using the unscented kalman filter.
Similar to using the extended Kalman filter, Neural Networks can also be trained through parameter estimation using the unscented Kalman filter.

The following Matlab project contains the source code and Matlab examples used for neural network training using the extended kalman filter.
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.

The following Matlab project contains the source code and Matlab examples used for gtl jetfuel ternplot with neural network.
Here the main2D.

The following Matlab project contains the source code and Matlab examples used for complex optimization of a recurrent neural network.
This package includes files for modelling nonlinear dynamic systems using a recurrent generalized neural network.