2005
DOI: 10.1016/j.sigpro.2004.11.002
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Constructive role of noise in signal detection from parallel arrays of quantizers

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Cited by 32 publications
(25 citation statements)
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“…They are also superior to power-law nonlinearities as tested in [6], and are much more easily implementable with electronic devices. The investigation of such saturating nonlinearities for stochastic resonance in arrays could reveal further useful potentialities for SNR amplification and also for other signal processing tasks [7], [16]. In the same direction, as other interesting nonlinearities to be tested, one could think of basic nonlinearities encountered in semiconductor…”
Section: Resultsmentioning
confidence: 99%
“…They are also superior to power-law nonlinearities as tested in [6], and are much more easily implementable with electronic devices. The investigation of such saturating nonlinearities for stochastic resonance in arrays could reveal further useful potentialities for SNR amplification and also for other signal processing tasks [7], [16]. In the same direction, as other interesting nonlinearities to be tested, one could think of basic nonlinearities encountered in semiconductor…”
Section: Resultsmentioning
confidence: 99%
“…This non-standard strategy to design suboptimal detectors based on two-state quantizers benefits from recent studies on the use of stochastic resonance and the constructive role of noise in nonlinear processes [9][10][11][12][13][14]. This paradoxical nonlinear phenomenon, has been intensively studied during the last two decades.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, another form of stochastic resonance was proposed in [9,10], with parallel arrays of two-state quantizers, under the name of suprathreshold stochastic resonance. This form in [9][10][11][12][13][14] applies to signals of arbitrary amplitude, which do not need to be small and subthreshold, whence the name. Different measures of performance have been studied to quantify the suprathreshold stochastic resonance: general information measures like the input-output Shannon mutual information [9], the input-output correlation coefficient [11], signal-to-noise ratios [11,13], in an estimation context with the Fisher information contained in the array output [12] or in a detection context with a probability of error [14].…”
Section: Introductionmentioning
confidence: 99%
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