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 Matlab Code For Artificial Neural Network 

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The form of a single layer feed forward neural network lends itself to finding the gradient. This is useful when the network is used for surrogate optimization or other algorithms that use gradients. Requires creating a file by modifying a NN toolbox file.



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 package includes files for modelling nonlinear dynamic systems using a recurrent generalized neural network. The learning scheme uses the complex method of nonlinear nonderivative optimization, thereby avoiding the problems of computing the...



The zip file contains
1. A 128x256 Regular (3,6) H matrix (if you need to simulate other codes, need to write your own code for generating those parity check matrices). The file '128x256regular_v6.mat' is for those using Matlab 6.5.
2....



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...



This is my lib for neural network. Include weights, neurons, neural layers, nets, simulation of nets, and back propagation supervising learning method. And also, its include a advance in neural teory: how to simplificate the combinatorial calculus.



SFAM is an incremental neural network classifier. It is a simple and fast version of Fuzzy ARTMAP (FAM). Both FAM and SFAM produce the same output given the same input.

References:
[1] Kasuba, T. (1993). "Simplified fuzzy...



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...



This is the code for calculating solid angle C, surface pressure ps, and field pressure pf coming out from a pulsating cylinder with radius of r and normal velocity vn in an unbounded two dimensional acoustic domain using the solution of Helmholtz...



A Ruby extension that provides a 2-Layer Back Propagation Neural Network, which can be used to categorize datasets of arbitrary size. The network can be easily (re-)stored to/from the hard disk.



Generic Neural Network. It's a class to build almost any type of Neural Networks, from a simple Perceptron to a SOM, supporting recurrence.



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...



A thin MATLAB wrapper for Git.

Short instructions:
Use this exactly as you would use the OS command-line verison of Git.

Long instructions are:
This is not meant to be a comprehensive guide to the...



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...



A fortran sample code which in Finite Difference Time Domain Method for Electromagnetics. - Kunz K.S., Luebbers R.J. book was translated to matlab code. For movie, a little bit code must be added into it. Especially it needs to vectorize for...



a simple matlab code to apply trail and error method .



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).



Learn how to use the Profiler tool, vectorized functions, and other tricks to writing efficient MATLAB code. This article includes how to convert any array into a column vector, bounding a value without if statements, and repeating/tiling a vector...



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.



Neuroph is friendly Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and nice GUI make it easy to learn and use.