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Neural Networks Articles



Computing Partial Functions and Fractal Decision Boundaries with Efficient Spiking Neural Nets (PDF)
A paper detailing a neural network model similar to standard spiking neural networks which does not require numerical integration. Source code included.
Forrest Briggs
Optimizing Functions on the Real Numbers
This article provides a guide to optimizing general functions of the form f : |Rn → |R. Techniques for solving this problem include analytical solution, gradient descent, annealing, evolution, particle swarm optimization and hybrid approaches.
Forrest Briggs
Universal Meta Optimization
Many problems in artificial intelligence such as training neural networks are optimization problems. The process of using an optimization algorithm to search all computable optimizers is meta optimization.
Forrest Briggs
Multi-Backpropagation Network: Concept and Modeling
A look at groupings of multiple backpropagation neural nets
Wan Hussain Wan Ishak
Some Reviews on Distributed Learning in Neural Networks
Training a single network is time consuming therefore distributed learning approaches such as hierarchical, multi-stage, parallel neural network computing are explored in this article.
Wan Hussain Wan Ishak


Applying Kohonen Networks
A look at how to apply networks, using a simple example of RGB mapping and a more complicated example using image classification.
James Matthews
Self Organizing Map AI for Pictures
This article is about creating an application to cluster and search for related pictures.
Casey Chesnut
Medical Diagnosis Using Neural Networks
Discusses using neural networks to aid diagnosis of several common medical conditions.
Norsarini Salim
Neural Networks in Anaemia Classification
A look at applying a multilayer perceptron to the classification of anaemia
Shuzlina Abd. Rahman
The Potential of Neural Networks in Medical Applications
Discusses the uses of neural networks within basic sciences, clinical medicine, signal processing and interpretation of medical images.
Wan Hussain Wan Ishak

Applications/Code  List Applications/Code articles in all topics

Kohonen-based Image Analysis using the Generation5 JDK
A look at how to write a Kohonen neural network to analyze and group similar photos.
James Matthews
Simple BMP File Analysis Using MLPs
This article looks at recognizing bitmapped smiley faces using MLPs.
Povilas Daniuđis
Neural Network explorer allows you to train and watch a neural network in real-time and tweak a variety of parameters.
Lucio Torres
Gesture Recognition Application (Delphi)
Delphi program that uses a neural network to recognize alphabetical gestures.
Michiel van Oudheusden
Data file only
Neural Network Explorer
Create an run your own neural networks in a graphical environment.
James Matthews
Kohonen Demonstrator - Java Applet
A Kohonen neural network self-organizes itself across a simple cartesian plane.
James Matthews
XOR Neural Network Code
Neural network code to solve the XOR problem.
Craig Furness
Data file only
Mouse Gestures Recognition
Feedforward multilayer neural network and mouse gesture recognition
Konstantin Boukreev
Optical Number Recognizor (ONR)
Uses perceptrons to recognize the digits 0-9.
James Matthews
Hopfield Image Recognizor (HIR)
Another simple program that uses a Hopfield associative neural network to recognize simple binary images.
James Matthews
PDA32 - Perceptron Demonstrator
Separates two groups of points uses a perceptron.
James Matthews
Simulated Annealing Demonstrator (SAD)
A very simple program that uses simulated annealing to find the minimum of a complicated function.
James Matthews
A simple C++ program that shows how to use a genetic algorithm to evolve neural network weights.
James Matthews
Back-Propagation: CBPNet
A simple C++ class implementing backpropagation.
James Matthews
Kohonen Demonstrator
A simple dialog-based Windows application that demonstrate a Kohonen self-organizing neural network.
James Matthews

Beginner  List Beginner articles in all topics

Back-propagation using the Generation5 JDK
A case study using the Generation5 JDK to understand feedforward neural networks and backpropagation.
James Matthews
Perceptrons are the simplest type of neural network.
James Matthews
Simple OCR Using Perceptrons
This articles looks at using perceptrons to recognize noisy images of the numbers 0-9.
James Matthews
Notes on Neural Network Learning and Training
An overview of learning and training for neural networks.
Wan Hussain Wan Ishak
Summing with Neural Networks
This article will try to explain how you can make a network capable of summing numbers as big as you want.
Stephen Tashev
BP Example: XOR Net
A step-by-step look at how the back-propagation algorithm works. Includes some C++ code to work with.
James Matthews
An Introduction to Neural Networks
Basic introduction to the theory of neural networks.
James Matthews

Character Recognition

Tablet PC OCR with Neural Network AI
This article will start out with an overview of neural networks and how I applied one to do custom OCR on the Tablet PC.
Casey Chesnut
Character Recognition with Hebbian Links
Discusses character recognition using neural networks using hebbian links.
Stephen Tashev


Neural Architecture Part 1: Simple Logic Functions
This article is going to discuss neural network construction from a different perspective than is usual in conventional approaches.
Christopher McCarley


Realtime Evolution of Agent Controllers in Games
After introducing the abstract concepts behind realtime evolutionary control of game agents, this paper discusses the application of these techniques to space invaders and a realtime strategy game similar to Warcraft. Source code included.
Forrest Briggs

Genetic Algorithms

Using Genetic Algorithms with Neural Networks
How to use genetic algorithms to evolve the weights in a neural network.
James Matthews

Projects  List Projects articles in all topics

Perceptron 'OR' Project
Train a perceptron to calculate the OR logic gate.
James Matthews
Simple OCR Project
Use a neural network to recognize digits and characters.
James Matthews

Theory  List Theory articles in all topics

Self-Organizing Nets
Introductory look at self-organizing neural networks - in particular, Kohonen networks.
James Matthews
Back-propagation for the Uninitiated
BP is a difficult algorithm to grasp at the best of times…this tutorials aims to provide a simple, but effective, introduction to back-propagation.
James Matthews
Simulated Annealing
A method taken from metallurgy that helps neural networks and genetic algorithms avoid local minima!
James Matthews
Neural Networks: Motivation, Theory and DANN
Motivation and theory of specific artificial neural networks are explained.
Daniel Eaton
Associative Neural Networks
An introduction to associative neural networks (ie., Hopfield Networks).
James Matthews
Multilayer Feedforward Network and the Backpropagation Algorithm
A complete look at the backpropagation algorithms.
Samuel Hsiung

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