Nonlinear enhancement of weak signals using optimization theory

Xingxing Wu, Zhong Ping Jiang, Daniel W. Repperger, Yi Guo

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

Abstract

Stochastic resonance (SR) is a phenomenon that performance of the nonlinear system can be improved with the addition of optimal amount of noise. Stochastic resonance has been increasingly used for signal processing. The output of the nonlinear bistable dynamic system with white Gaussian noise input can be used to restore the weak input signal, if the similarity between the input signal and the output can be maximized. This paper will first use the optimization theory to show that the normalized power norm describing the similarity will reach a larger maximum when tuning both system parameters and noise intensity, compared with that of only adjusting noise intensity (classical stochastic resonance) or only adjusting system parameters. Then, computer simulations are performed to verify this proposal and demonstrate its application in signal processing.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006
Pages66-71
Number of pages6
DOIs
StatePublished - 2006
Event2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006 - Luoyang, China
Duration: Jun 25 2006Jun 28 2006

Publication series

Name2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006
Volume2006

Other

Other2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006
CountryChina
CityLuoyang
Period6/25/066/28/06

Keywords

  • Optimization
  • Signal processing
  • Stochastic resonance

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Mechanical Engineering
  • Control and Systems Engineering

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