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A SEMINAR ON

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A SEMINAR ON ‡ARTIFICIAL NEURAL NETWORK \ NEURAL NETWORK«  What is a Neural Network?  An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems such as the brain, processes information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like p
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  A SEMINAR ON ‡ARTIFICIAL NEURAL NETWORK \  NEURAL NETWORK«  What is a Neural Network?  An Artificial Neural Network (ANN) is an information processingparadigm that is inspired by the way biological nervous systems suchas the brain, processes information. The key element of this paradigmis the novel structure of the information processing system. It iscomposed of a large number of highly interconnected processingelements (neurons) working in unison to solve specific problems.ANNs, like people, learn by example. An ANN is configured for aspecific application, such as pattern recognition or data classification,through a learning process. Learning in biological systems involvesadjustments to the synaptic connections that exist between theneurons. This is true of ANNs as well.  H istory of Neural Networks  The study of the human brain is thousands of years old. With the advent of modernelectronics, it was only natural to try to harnessthis thinking process. The first step towardartificial neural networks came in 1943 whenWarren McCulloch, a neurophysiologist, and ayoung mathematician, Walter Pitts, wrote apaper on how neurons might work. Theymodeled a simple neural network with electricalcircuits.  Why use neural networks? ‡ Neural networks, with their remarkable ability to derive meaning fromcomplicated or imprecise data, can be used to extract patterns and detecttrends that are too complex to be noticed by either humans or other computer techniques. A trained neural network can be thought of as an expert in the category of information it has been given to analyses. Thisexpert can then be used to provide projections given new situations of interest and answer what if questions. Other advantages include:-  Adaptive learning: An ability to learn how to do tasks based on the datagiven for training or initial experience.  Self-Organisation: An ANN can create its own Organisation or representation of the information it receives during learning time.  in monitoring:± networks have been used to monitor ‡ the state of aircraft engines. By monitoring vibration levels andsound, early warning of engine problems can be given.
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