VLSI implementation of a neural network for solving linear second order parabolic PDE

Sung T. Moon, Bo Xia, Ronald G. Spencer, Gunhee Han, Edgar Sánchez-Sinencio

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

We have proposed an implementation of a cellular neural network to solve linear second order parabolic partial differential equations. This paper describes the underlying theory, circuit architecture and techniques employed to improve accuracy and throughput. A modified time-multiplexing scheme is applied to provide an area efficient solution. Simulation results and comparison are also included to illustrate the circuit performance.

Original languageEnglish
Pages836-839
Number of pages4
Publication statusPublished - 2000 Dec 1
Event43rd Midwest Circuits and Systems Conference (MWSCAS-2000) - Lansing, MI, United States
Duration: 2000 Aug 82000 Aug 11

Other

Other43rd Midwest Circuits and Systems Conference (MWSCAS-2000)
CountryUnited States
CityLansing, MI
Period00/8/800/8/11

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All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Cite this

Moon, S. T., Xia, B., Spencer, R. G., Han, G., & Sánchez-Sinencio, E. (2000). VLSI implementation of a neural network for solving linear second order parabolic PDE. 836-839. Paper presented at 43rd Midwest Circuits and Systems Conference (MWSCAS-2000), Lansing, MI, United States.