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sss - Neural Network Design A Preview S.Saranya cse Gitam...

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Neural Network Design- A Preview S.Saranya K.Silpa ¾ cse ¾ cse Gitam University Gitam University [email protected] [email protected] Abstract: Neural network is a computing architecture that consists of massively parallel interconnections of simple computing elements called “Neurons”. A neuron is the basic functional unit of the brain. Neural Network consists of a set of neurons are connected in a random manner. In this paper,we propose a method to implement the operational concepts of the nervous system and functions of neurons using hardware components. Basically these networks have the capacity to learn, memorize and create relationships among data . 1. Introduction In the year 1936, John von Neumann proposed the notion of a simple neural network. In 1943, as an attempt to develop hardware for neural networks, scientists like Warren McCollum and Watter Pits designed an “Artificial Neuron”.Subsequently, many people attempted to realize neuron models in the form of electronic circuits. One such model was proposed by Leon D. Harmon in the year 1961. With this model, he performed experiments in which he simulated many functional characteristics of neuron. In this paper, we propose to realize neuron models as nano devices based molecular interconnects. 2. What is Artificial Neural Network? The term 'neural network' is in fact a biological term, and what we refer to as neural networks should really be called Artificial Neural Networks (ANNs). ANN is a modeling technique based on the observational behavior of biological neurons and used to mimic the performance of the same. It can also be considered as a computing system inspired by human brain that learns and performs functions rather than having a program in it. In this network “Artificial Neurons” serve as processing element units. Artificial Neurons (AN) form the basic unit in ANN. Each AN may have one or more inputs but only one output. Neural Networks are a different paradigm for computing: von Neumann machines are based on the processing/memory abstraction of human information processing. neural networks are based on the parallel architecture of animal brains . 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 A biological neuron may have as many as 10,000 different inputs, and may send its output (the presence or absence of a short-duration spike) to many other neurons. Neurons are wired up in a 3- dimensional pattern. Real brains, however, are orders of magnitude more complex than any artificial neural network so far considered. The mathematical model of an Artificial Neuron is as below:
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Here X1, X2 and X3 are the inputs which are fed to a neuron after multiplying weighted factors W1, W2 and W3 correspondingly. Yi is the sum of weighted inputs. And Y0 is the output.
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