BY
V.K.DEEPAK
NEURAL NETWORKS
INTRODUCTION
Neural Network or more appropriately Artificial Neural Network is basically a mathematical model of what goes in our mind(or brain).The brain of all the advanced living creatures consists of neurons, a basic cell, which when interconnected produces what we call Neural Network.The sole purpose of a Neuron is to receive electrical signals, accumulate them and see further if they are strong enough to pass forward.
DEFINITION
Neural network is a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.Neural networks are adaptive statistical models based on an analogy with the structure of the brain.Neural networks are a form of multiprocessor computer system, with simple processing elements a high degree of interconnection,simple scalar messages,adaptive interaction between elements
BASICS OF NEURAL NETWORKS
Neural neworks are typically organized in layers.Layers are made up of a number of interconnected 'nodes' which contain an 'activation function'.Patterns are presented to the network via the _'input _layer‘.Input layer communicates to one or more 'hidden layers' where the actual processing is done via a system of weighted 'connections‘.The hidden layers then link to an 'output layer' where the answer is output .
A BASIC MODEL OF NEURAL NETWORK
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LAYERS OF NEURAL NETWORK
INPUT LAYER
This layer takes the inputs(the values you pass) and forwards it to hidden layer.You can just imagine input layer as a group of neurons whose sole task is to pass the numeric inputs to the next level.
HIDDEN LAYER
This layer is the real thing behind the network. Without this layer, network would not be capable of solving complex problems.There can be any number or middle or hidden layers.The number of neurons in this layer is crucial. There is no formula for calculating the... [continues]

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