Custom VLSI ASIC for automotive applications with recurrent networks

Author

Tawel, R. ; Aranki, N. ; Puskorius, G.V. ; Marko, K.A. ; Feldkamp, L.A. ; James, J.V. ; Jesion, G. ; Feldkamp, T.M.

Author_Institution

Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA

Volume

1

fYear

1998

fDate

4-8 May 1998

Firstpage

598

Abstract

Demands on the performance of vehicle control and diagnostic systems are steadily increasing as a consequence of stiff global competition and government mandates. Neural networks provide a means of creating control and diagnostic strategies that will help in meeting these demands efficiently and robustly. This paper describes a VLSI design that permits such networks to be executed in real time as well as the application in misfire detection, that served as a focus for the collaborative effort

Keywords

VLSI; application specific integrated circuits; automobiles; automotive electronics; fault diagnosis; neural chips; neural net architecture; neurocontrollers; recurrent neural nets; ASIC; VLSI; automobiles; automotive electronics; fault diagnosis; misfire detection; neurocontrol; recurrent neural networks; Application specific integrated circuits; Automotive applications; Computer architecture; Control systems; Hardware; Laboratories; Multilayer perceptrons; Neural networks; Neurons; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.682346

Filename

682346