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Design And Performance Analysis Of And Gate Using Synaptic Inputs For Neural Network Application

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DESIGN AND PERFORMANCE ANALYSIS OF AND GATE USING SYNAPTIC INPUTS FOR NEURAL NETWORK APPLICATION
[1]S.SOUNDARYA [2] VAMSHI.G [3] SOUNDARAJAN.M [4] RAMKUMAR.A
[1] [2] [3] Students, ece department, saveetha school of engineering, Chennai
[4] Asst.prof, ece department, Saveetha School of engineering, Chennai

ABSTRACT
Logic gates are one of the main constituents to design and integrate as a chip. With advent of vision and method in neural network, the intricacy can be clear alongside this knowledge to a remarkable extent. The intention of this paper is to focus on how to design a perceptron that is nothing but a single layer feed forward neural network to purpose as an AND gate and to examine its performance. Firstly, the background of
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It is a kind of linear classifier, i.e. an association algorithm that makes it forecasts established in a linear predictor purpose joining a set of weights alongside the feature vector. In this paper, the mathematical background of neural network will be studied firstly. Then, Neural Web Toolbox in MATLB® will be utilized to develop the neural web for assisting the analyzing of an AND gate.

II.BASIC CONCEPTS
II.A NEURON
The human brain is a collection of concerning 10 billion interconnected neurons. Every single neuron is a cell that uses biochemical replies to accord, procedure and send information. It is an electrically excitable cell that procedures and transmits data across mechanical and chemical signals. These signals amid neurons transpire via synapses, enumerated connections alongside supplementary cells. Neurons can link to every single supplementary to form neural networks. A neuron’s dendritic tree is related to a thousand bordering neurons. As one of those neuron fires, an affirmative or negative price is consented by one of the dendrites.
II.B NEURAL NETWORK
Neural network is a computer arrangement of biological neurons, composed of nonlinear computational agents working in parallel. A neuron’s dendritic tree is related to a thousand bordering neurons. As one of those neurons fire, an affirmative or negative price is consented by one of the dendrites. The strengths of all the consented prices are added jointly across the procedures of spatial and temporal
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