Design of a neuro-fuzzy chip using adaptive multimode approaches for an intelligent car-backing system

Shao Hua Lee, Jeen-Shing Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper pres1ents a new approach to design an adaptive multimode neuro fuzzy chip (AMNFC) with on-chip learning and highly-efficient resource utilization capabilities for a car-backing system. The design process is performed by a high-level datapath synthesis that is based on an optimal scheduling and a resource allocation algorithm. A novel data flow graph (DFG) scheduling algorithm suitable for parallel structure computation has been developed for designing a neuro-fuzzy chip. The proposed algorithm fulfills two major objectives. First, it simultaneously optimizes both the schedule and allocation of functional units, registers, and multiplexers with respect to a minimal cost of the hardware resources and the total time of execution. Second, it implements an adaptive multimode neural-fuzzy system with reconfiguration capability. Computer simulations and experimental results have successfully validated the effectiveness of the proposed design approach for a car-backing system.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
Pages3799-3804
Number of pages6
DOIs
Publication statusPublished - 2004 Dec 1
Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague, Netherlands
Duration: 2004 Oct 102004 Oct 13

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume4
ISSN (Print)1062-922X

Other

Other2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
CountryNetherlands
CityThe Hague
Period04-10-1004-10-13

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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