The Psychology of Beauty Brains The Psychology of Video Games Neuroskeptic Neural Networks Many concepts related to the neural networks methodology are best explained if they are illustrated with applications of a specific neural network program. Therefore, this section contains many references to STATISTICA Neural Networks, a particularly comprehensive neural networks application available from StatSoft. Preface Neural networks have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics. Power. Neural networks are also intuitively appealing, based as they are on a crude low-level model of biological neural systems. Applications for Neural Networks Detection of medical phenomena. The Biological Inspiration The brain is principally composed of a very large number (circa 10,000,000,000) of neurons, massively interconnected (with an average of several thousand interconnects per neuron, although this varies enormously).
Mind Hacks Mind Hacks Neural Networks Abstract This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. Contents: 1. 1.1 What is a neural network? 1.2 Historical background 1.3 Why use neural networks? 1.4 Neural networks versus conventional computers - a comparison 2. 2.1 How the Human Brain Learns? 2.2 From Human Neurones to Artificial Neurones 3. 3.1 A simple neuron - description of a simple neuron 3.2 Firing rules - How neurones make decisions 3.3 Pattern recognition - an example 3.4 A more complicated neuron 4. 4.1 Feed-forward (associative) networks 4.2 Feedback (autoassociative) networks 4.3 Network layers 4.4 Perceptrons 5. 5.1 Transfer Function 5.2 An Example to illustrate the above teaching procedure 5.3 The Back-Propagation Algorithm 6. 6.1 Neural networks in practice 6.2 Neural networks in medicine 6.3 Neural networks in business 7. 1. 2. 3.
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