Pulsed Neural Networks

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Presentation transcript:

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

Overview Type notes here

Challenging Problems Type notes here

Challenging Problems Image recognition in varied settings Speech recognition in noise Robotic control and navigation Type notes here

Artificial Neural Networks Type notes here

Biological Neuron Type notes here

Biological Neuron Type notes here

Perceptron Type notes here

Perceptron Response Type notes here

Linear Separability Type notes here

Linear Separability Type notes here

Logic Gates Type notes here

Parallel Processing Type notes here

Sigmoid Neuron Type notes here

Sigmoid Neuron Response Type notes here

Neural Network Type notes here

Neural Network Type notes here

Universal Approximation Type notes here

Universal Approximation Type notes here

Universal Approximation Type notes here

Function Approximations Type notes here

Learning Type notes here

Gradient Descent Type notes here

Local Minima Type notes here

Backward-Error Propagation Type notes here

Dynamic Networks Type notes here

Dynamic Networks Type notes here

Learning through Time Type notes here

Learning through Time State v1 Adaptive Critic x1 p v16 ^ r w1 0 or 1 noise x1 p delay v16 l reward = ±1 decay r ^ a b w1 Associative Search noise q y x16 w16 Type notes here x x q q ±F

Pulsed Networks Type notes here

Pulsed Neuron Type notes here

Pattern Processing Type notes here

Response Regions Type notes here

Pattern Windows Type notes here

Pattern Windows Type notes here

Dynamic Pulsed Networks Type notes here

Applications Type notes here

Speech Recognition Type notes here

Auditory System Type notes here

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

Title Type notes here