Advisor

Marek Perkowski

Date of Award

5-5-1995

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Electrical and Computer Engineering

Department

Electrical and Computer Engineering

Physical Description

1 online resource (viii, 136 p.)

Subjects

Algebra, Boolean -- Data processing, Logic design -- Data processing

Abstract

Cube Calculus is an algebraic model popular used to process and minimize Boolean functions. Cube Calculus operations are widely used in logic optimization, logic synthesis, computer image processing and recognition, machine learning, and other newly developing applications which require massive logic operations. Cube calculus operations can be implemented on conventional general-purpose computers by using the appropriate "model" and software which manipulates this model. The price that we pay for this software based approach is severe speed degradation which has made the implementation of several high-level formal systems impractical. A cube calculus machine which has a special data path designed to execute multiplevalued input, and multiple-valued output cube calculus operations is presented in this thesis. This cube calculus machine can execute cube calculus operations 10-25 times faster than the software approach. For the purpose of ensuring the manufacturing testability of the cube calculus machine, emphasize has been put on the testability design of the cube calculus machine. Testability design and testability analysis of the iterative logic unit of the cube calculus machine was accomplished. Testability design and testability analysis methods of the cube calculus machine are weli discussed in this thesis. Full-scan testability design method was used in the testability design and analysis. Using the single stuck-at fault model, a 98.30% test coverage of the cube calculus machine was achieved. A Povel testability design and testability analysis approach is also presented in this thesis.

Description

If you are the rightful copyright holder of this dissertation or thesis and wish to have it removed from the Open Access Collection, please submit a request to pdxscholar@pdx.edu and include clear identification of the work, preferably with URL

Persistent Identifier

https://archives.pdx.edu/ds/psu/28540

Share

COinS