Analog hardware for learning neural networks

US5056037A · kind A · utility

Assignee

• The United States of America as represented by the Administrator of the National Aeronautics and Space Administration · US

Inventor

• Silvio P. Eberhardt · Pasadena, US

Key dates

• Filing date: Dec 28, 1989
• Grant date: Oct 8, 1991
• Expiry date: Dec 28, 2009

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/065
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

This is a recurrent or feedforward analog neural network processor having a multi-level neuron array and a synaptic matrix for storing weighted analog values of synaptic connection strengths which is characterized by temporarily changing one connection strength at a time to determine its effect on system output relative to the desired target. That connection strength is then adjusted based on the effect, whereby the processor is taught the correct response to training examples connection by connection.