Pulsed Neural Networks Neil E. Cotter ECE Department University of Utah.

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Presentation transcript:

Pulsed Neural Networks Neil E. Cotter ECE Department University of Utah

Overview

Challenging Problems

Image recognition in varied settings Speech recognition in noise Robotic control and navigation

Artificial Neural Networks

Biological Neuron

Perceptron

Perceptron Response

Linear Separability

Logic Gates

Parallel Processing

Sigmoid Neuron

Sigmoid Neuron Response

Neural Network

Universal Approximation

Function Approximations

Learning

Gradient Descent

Local Minima

Backward-Error Propagation

Dynamic Networks

Learning through Time

 ±F  x x  State 0 or 1 x1x1 x 16 w1w1 w 16 noise y v1v1 v 16 noise delay reward = ±1 p  decay r ^  Adaptive Critic Associative Search

Pulsed Networks

Pulsed Neuron

Pattern Processing

Response Regions

Pattern Windows

Dynamic Pulsed Networks

Applications

Speech Recognition

Auditory System

Research Opportunities Mathematically describe pattern processing Devise pattern-learning algorithms Build circuits

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