Note: One of the easiest ways to find good resources on neural networks is to go to www.about.com or www.infind.com and enter search query: "neural networks."
Another GREAT list of Neural Network Resources ("If it's on the web, it's listed here") is http://www.geocities.com/SiliconValley/Lakes/6007/Neural.htm

• FAQs: Frequently Asked Questions: Newsgroup:This site contains detailed but comprehensible answers to common questions about NNs. Particularly useful for me was the question "What can you do with an ANN?" It also contains an excellent set of links to online NN resources. Highly recommended for content, if not for beauty of site design.

• Fabulous NN introduction: Artificial Neural Networks Technology (from the Department of Defense Information Analysis Center):An excellent introduction to the basic principles of neural networks, this article has many clear graphics and non-mathematical, but thorough, explanations. It investigates the basic architecture of a neural network, including the various configurations and learning mechanisms, and also discusses the history and future applications of the neural network.

• A textbook and network simulator in one: Brain Wave:This introductory, online textbook also contains an interactive applet for making one's own simple networks. This text contains many excellent, clear graphics, and non-technical explanations of the various neural net architectures.

• Fun, simple applets: Web Applets for Interactive Tutorials on Artificial Neural Learning

• Animated neuron and NN Introduction: An Introduction To Neural Networks:This page contains a great animated gif of a biological neuron, and also includes a general introduction to neural networks.

• General Introduction: Generation 5'sIntroduction to Neural Networks:This article provides an introduction to neural networks for a non-technical audience.

• Introduction to Kohonen networks: Kohonen Networks:This article deals with one specific type of neural network, the Kohonen network, which is used to execute unsupervised learning. In unsupervised learning, there is no comparison of the network's answer to specific desired output, and the simulated neurons have the property of self-organization.

• Introduction and comparison with Von Neumann: An Introduction to Neural Networks:Dr Leslie Smith presents a good comparison between the advantages and disadvantages of the von Neumann architecture and neural networks, and also provides a quick survey of different kinds of networks. These include the BP network, RGF network, simple perceptron network, and Kohonen network. The article also examines where neural networks are applicable and where they may possibly be applied in the future.

• Somewhat Technical NN Description: Statsoft's Neural Networks:This article provides a lengthy and somewhat technical description of neural networks. It looks at RBF networks, probabilistic neural networks, generalized regression neural networks, linear networks, and Kohonen networks. It looks at the artificial model of neural networks and how the human brain is modeled with neural networks. It also examines feedforward structures and the structures most useful in solving problems.

• Applets for XOR and Kohonen: The HTML Neural Net Consulter.

• Intro from ZSolutions, a NN-provider: Introduction to Neural Networks:Using a simple example of a neural network developed to predict the number of runs scored by a baseball team, this article investigates the architecture and potential uses of neural networks. It also serves as promotional material: Z Solutions provides neural networks for corporations.

• Intro 2 from ZSolutions, a NN-provider: Want to Try Neural Nets?A somewhat propaganda-esque document for a neural networking company, this article nonetheless provides a good introductory survey of neural networks and the potential for implementing them in the real world.

• Fuzzy Logic Information: FuzzyTech:a vast resource for information, simulations, and applications of fuzzy logic.

• Information on over 50 NN applications: BrainMaker Neural Network Software:Great list of examples of specific NN applications regarding stocks, business, medicine, and manufacturing.

• Applet for 8-queens problem: 8-queens problem and neural networks

• Applet for Travelling Salesman: Elastic Net Method for Travelling Salesman Problem:The elastic net is a kind of neural networks which is used for optimization problems; this applet demonstrates its use applied to the Travelling Salesman Problem.

• Handwriting Recognition Applet: Artificial Neural Network Handwriting Recognizer:This applet demonstrates neural networks applied to handwriting recognition. Users train a neural network on 10 digits of their handwriting and then test its recognition accuracy.

• A few applets: Takefuji LabsNeural demo by Java.

• NNs as Information Analyzers: Technology Brief: Artificial Neural Networks as Information Analysis Tools:The article discusses how neural networks, as information analysis tools, can be used in the medical industry, the environment, security and law enforcement, and mechanical system diagnosis.
 
• NNS for Medical Diagnosis: Technology Brief: Computer Assisted Medical Diagnosis:This article looks at the ways in which a neural network can assist doctors in medical diagnoses. It investigates uses in the cardiovascular system, diagnosing coronary artery disease, and chemical analysis.

• Applet for Travelling Salesman: Travelling Salesman ProblemThis applet demonstrates a neural network applied to a 2-D travelling salesman problem.

• Applet for Image Compression: Image Compression using Backprop.

 
• Fuzzy Logic Information: FuzzyTech:a vast resource for information, simulations, and applications of fuzzy logic.

• Technical / Philosophical Paper: Neural Networks and the Computational Brain


• Database of Common Sense: ThoughtTreasure:ThoughtTreasure is a database of 25,000 concepts, 55,000 English and French words and phrases, 50,000 assertions, and 100 scripts, which is attempting to bring natural language and commonsense capabilities to computers.  The conclusions page is especially clear and concise.

 
• Long and thorough paper from Yugoslavia: Hierarchical Neural Networks and Brainwaves: Towards a Theory of Consciousness:This paper gives "a comparative biocybernetical analysis of the possibilities in modeling consciousness and other psychological functions (perception, memorizing, learning, emotions, language, creativity, thinking, and transpersonal interactions!), by using biocybernetical models of hierarchical neural networks and brainwaves."

• Mehrotra, Kishan, Chilukuri Mohan, and Sanjay Ranka. Elements of Artificial Neural Networks. Boston: MIT Press, 1997.

• Skapura, David M. Building Neural Networks. Menlo Park, CA: Addison-Wesley Publishing Company, 1996.   This is an introductory textbook for the construction of actual neural networks. It investigates many of the potential uses of neural networks in a manner aimed at allowing students themselves to create these networks. Sample C code is also provided.

<< to top>>