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

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:

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.