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on sizes and they can be designed to operate in nano /femto sizes leading to extreme low power
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rate, momentum factor, selection of network size etc Thus it becomes very much essential to have some concrete guard Lines for selecting the network. Further, there is .................. [:=> Show Contents <=:] | |||

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ct value ci whenever its code is present the output of the vertex code generator we use a standard
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A MLP consists of several layers of processing units that compute a nonlinear function of the
internal product of the weighted input patterns. These types of network can deal with nonlinear
relations between the variables; however, the existence of more than one layer makes the weight
adjustment process for problem solution difficult. BACK PROPOGATION ALGORITHM This method has proven highly successful in training of multilayered neural networks. The network is not just given reinforcement for how it is doing on a task. Information about errors is also filtered back through the system an.................. [:=> Show Contents <=:] | |||

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of feeder reconfiguration to reduce power loss, by using A...................[:=> Show Contents <=:] | |||

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a few of which will be dealt in the consequent sections and then its limitations. The main question
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that can be algorithms or actual hardware that are modeled after the functioning of human brain.
Most Neural Networks have some sort of training rule whereby the weights of connections are adjusted
on the basis of presented patterns. In other words, Neural Networks learn from examples, just like
children learn to recognize dogs from examples of dogs and exhibit some structural capability for
generalization. The most significant aspects of Neural Networks are that they allow the computer to learn and they have the potential for parallelism. This means that they allow the computer to solve m.................. [:=> Show Contents <=:] |

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