Neural Networks An Introduction.

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Presentation transcript:

Neural Networks An Introduction

An Introduction to Neural Networks A Neuron An Introduction to Neural Networks

Computer Representation Output= a(n) = a(pw+b) An Introduction to Neural Networks

A Single Neuron with Multiple Inputs An Introduction to Neural Networks

Single Layer Neural Network with Multiple Neurons An Introduction to Neural Networks

Multiple Layer Neural Network An Introduction to Neural Networks

An Introduction to Neural Networks Activation Functions Hard Limit a = 0 n < 0 a = 1 n >= 0 Symmetrical Hard Limit a = -1 n < 0 a = +1 n >= 0 Saturating Linear a = n 0 <= n <= 1 a = 1 n > 1 An Introduction to Neural Networks

An Introduction to Neural Networks Activation Functions Linear a = n Symmetric Saturating Linear a = -1 n < -1 a = n -1 <= n <= 1 a = 1 n > 1 Log-Sigmoid a = 1 1+ e-n An Introduction to Neural Networks

An Introduction to Neural Networks Activation Functions Hyperbolic Tangent Sigmoid a = en - e-n en + e-n Positive Linear a = 0 n < 0 a = n n >= 0 Competitive a = 1 neuron with max n a = 0 all other neurons An Introduction to Neural Networks

The History of Development of Neural Networks The Beginning of Neural Networks (1940's) McCulloch Pitts Neuron Hebb Learning The First Golden Age of Neural Networks (1950's and 1960's) Perceptrons Adaline The Quiet Years: 1970's Kohonen Anderson Grossberg Carpenter Renewed Enthusiasm: 1980's Backpropagation Hopfield nets Neocognitron Boltzman machine Hardware Implementation An Introduction to Neural Networks

Developing a Neural Network System Choose a neural network architecture Train the neural network using a training set Apply the neural network to identify patterns. This involves implementing the application algorithm An Introduction to Neural Networks

Choosing a Neural Network Architecture Identify the number of inputs Number of network inputs = number of problem inputs. Identify the number of outputs Number of neurons in output layer = number of problem outputs. The output layer transfer function is partly determined by problem specification of the outputs. An Introduction to Neural Networks