Hierarchical adaptive state machine for emulating and augmenting software

Michael Heimlich (Inventor), Kenneth St Hilaire (Inventor)

Research output: Patent

Abstract

The present invention defines a method for emulating an iterated process represented by a series of related tasks and a control mechanism that monitors and enables the iterative execution of those tasks until data associated with the process converges to predetermined goals or objectives. The invention defines a method in which fuzzy neural networks and discreet algorithms are applied to perform the process tasks and in which configurable, reloadable finite state machines are applied to control the execution of those tasks. In particular, the present invention provides a method for emulating the process of designing integrated circuit (IC) applications and printed circuit board (PCB) applications for the purpose of simulating, emulating, analyzing, optimizing and predicting the behavioral and physical characteristics of the application at the earliest possible stage of the process. The invention applies fuzzy neural networks and configurable, reloadable finite state machines to emulate the IC or PCB design process, enabling the invention to emulate the the computer aided design (CAD) tools used to perform the design process tasks as well as the individuals using those tools. By emulating the combination of man and machine performances, the invention can more accurately predict the results of a given task than tools that consider only the machine element. The invention also provides a means to adapt the performance and behavior of any element of the invention using historical data compiled from previous design or manufacturing experiences, allowing the invention to incorporate the knowledge gained from previous designs into current designs.
Original languageEnglish
Patent number5903886
IPCG06F 17/50
Priority date30/04/96
Publication statusPublished - 11 May 1999
Externally publishedYes

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