The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 53-306
Full Name: Gencheng Guo
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: 9107 - 116 Street, Edmonton
Country: CANADA
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E-mail address: gencheng@ece.ualberta.ca
Other E-mails: guogencheng@126.com
Title of the Paper: An adaptive stochastic-resonance-based detector and its application in watermark extraction
Authors as they appear in the Paper: Gencheng Guo and Mrinal Mandal
Email addresses of all the authors: gencheng@ece.ualberta.ca, mandal@ece.ualberta.ca
Number of paper pages: 17
Abstract: In this paper, we explore a stochastic resonance (SR) based detector using bistable system (BS) to detect a binary pulse amplitude modulated (PAM) signal embedded in non-Gaussian noise. Through the example of BS based watermark extraction, we show that a reliable performance cannot be obtained if the BS parameters are determined by traditional tuning technique. The key observation is that the BS parameters are not sensitive to the pdf of the noise but to the variance of the noise and the amplitude of the signal. That makes it possible to determine the BS parameters in advance and an adaptive BS can be constructed based on the estimated amplitude of the watermark (signal) and the variance of the DCT coefficients (noise). Experimental results show that the performance obtained from the proposed adaptive stochastic-resonator-based detector is stable and provides superior performance compared to the existing BS based watermark schemes and the Gaussian based maximum lik!
elihood (ML) detector.
Keywords: Signal detection, Stochastic resonance, Bistable system, Optimal parameters, Watermark extraction.
EXTENSION of the file: .pdf
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How Did you learn about congress: detection, signal and system analysis, statistic signal analysis
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