Introduction to neural networks PDF Print E-mail
Technology - Artificial intelligence

Neural networks introduction


Introduction to neural networks

Like nanotechnology, neural networking is the use of technology to design and manufacture  (intelligent) machines, built for specific purposes, programmed to perform specific tasks. However, unlike nanomachines, neural networks are designed to work like a nerve cell system, more similar to the workings of the human or biological brain in in its physical form. See also robots and artificial intelligence.

With today's complex society there is a growing need for semi-autonomous systems that can do some of the thinking and controlling for us. The logic of a neural network approximates our own thinking structures the closest and gives us the opportunity to endow specific intelligence to designed control systems. See also cybernetics.

Want to know more? Follow one or several of the free tutorials on the right to gain knowledge about artificial neural networks.


A typical Neuron.
(c) NewWave Intelligent Business Systems (SG)

Tutorials on Neural Networks

comp.ai.neural-nets FAQ (7 parts)
Neural Networks Tutorial, Computer Science at the College of Charleston (US)
Advanced Neural Networks Tutorial, PMSI (F), including Saxon 4.4 Demos - Prediction, classification, modeling Parabola, a program to test neural network behavior.
Artificial Neural Networks Technology, Department of Defense (US)
An Introduction to Neural Networks, Dept. of Electrical & Computer Engineering, University of Maryland (US)
Crash introduction to Artificial Neural Networks, University of Massachusetts at Lowell (US)
Neural Networks, Dept. of Computing, Imperial College, London (UK)
An Introduction to Neural Networks, Centre for Cognitive and Computational Neuroscience, Department of Computing and Mathematics, University of Stirling (UK)

Neural Network applications

What exactly are neural networks used for? Artificial neural networks are powerful tools for use in classification, empirical modeling and pattern recognition, for example. They are useful in fields as diverse as financing and investing, business, medical, sports, science and manufacturing.

They are used to "predict" the rise and fall of stock prices, race course predictions (horse and dog racing), hospital length of stay, weather forecasting, earthquake prediction, plastics and concrete testing, gene recognition.

 

In the field of robotics and artificial intelligence, artificial neural networks are crucial to the development of the robotic brain, its logic, its ability to learn, its processing and analyses of input.

Neural Network applications

Training Neural Networks for Speech Recognition, Oregon Graduate Institute of Science and Technology (US)
Neural network applications in ecology and oceanography, Department of Biology, University of Rome (I)
Neural Network - as a Pattern Classifier and Feature Selector, PrettyView (J)
Neural Networks applications, the sudden rise of Neurocomputing, NewWave Intelligent Business Systems (SG)

 

 

Neural network software and programming

In view of the complexity in designing neural networks it is not surprising that computers play a major role. No computer without software and applications made for working with neural networks, such as design, logic and implementation, are becoming more plentiful and mainstream. However, this is a growth industry and as such there always room for writing your own.

Neural network software

Joone - Joone is a free neural network frame, to create, train and test neural nets.

Neural network hardware

 

On the hardware front of neural network systems great strides have been made. Mimicking or simulating a neural network can be done in different ways. The biological approach necessitates the need to grow and condition or program actual biological nerve cells into specific behavior.

 

Neural network hardware and processors

Accurate Automation - NNP's, neural network processors and equipment

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