DTIC ADA1022217: Computing with Connections pdf

DTIC ADA1022217: Computing with Connections

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There is a rapidly growing interest in problem-scale parallelism, both as a model of animal brains and as a paradigm for VLSI. Work at Rochester has concentrated on connectionist models and their application to vision. This paper lays out a framework for dealing with such problems. The framework is built around computational modules, the simplest of which are termed p-units. We develop their properties and show how they can be applied to a variety of problems. To show how the framework can be applied to computational problems in vision, two specific examples are developed in some detail. In the first, we describe how spatially distributed data can be associated with a complex concept. In the second, we discuss the shape from shading problem and show how a global parameter, such as light source position, interacts with the calculation of a spatially distributed parameter such as surface orientation.

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• Creator/s: Defense Technical Information Center
• Date: 4/1/1981
• Year: 1981
• Book Topics/Themes: DTIC Archive, Feldman, J A, ROCHESTER UNIV NY DEPT OF COMPUTER SCIENCE, *MATHEMATICAL MODELS, *BRAIN, *COMPUTER LOGIC, *COMPUTER ARCHITECTURE, DATA BASES, COMPUTERIZED SIMULATION, COMPUTER COMMUNICATIONS, PARAMETERS, EIGENVALUES, PARALLEL PROCESSING, COMMUNICATIONS NETWORKS, VECTOR ANALYSIS, ARTIFICIAL INTELLIGENCE, VISUAL PERCEPTION, NETWORK FLOWS

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