Neural net guesses appliances

Eecient Neural Net --evaluators

cient Neural Net

We show how eld-programable gate arrays can be used to eeciently implement neural nets. By implementing the training phase in software and the actual application in hardware, connicting demands can be met: training beneets from a fast edit-debug cycle, and once the design has stabilized, a hardware implementation results in higher performance. While neural nets have been implemented in hardware...

Artificial neural net attractors

ÐAesthetically appealing patterns are produced by the dynamical behavior of arti®cial neural networks with randomly chosen connection strengths. These feed-forward networks have a single hidden layer of neurons and a single output, which is fed back to the input to produce a scalar time series that is always bounded and often chaotic. Sample attractors are shown and simple computer code is prov...

Neural Networks with Java: neural net overview

What are neural nets? The biological model: The human brain The components of a neural net What they can and where they fail The learning process What means "learning" refering to neural nets? Supervised and unsupervised learning Forwardpropagation Backpropagation Selforganization

Fast Neural Net Simulation with

This paper describes the implementation of a fast neural net simulator on a novel parallel distributed-memory computer. A 60-processor system, named MUSIC, 1 is operational and runs the back-propagation algorithm at a speed of 247 million connection updates per second (continuous weight update) using 32 bit oating-point precision. This is equal to 1 GGops sustained performance. The complete sys...