Enhanced coding for exponentially distributed signals using suprathreshold stochastic resonance

نویسندگان

  • Aruneema Das
  • Nigel G. Stocks
  • Evor L. Hines
چکیده

Our previous work on stochastic resonance (SR) in threshold based systems proved that the SR effect is dependent on the nature of the input signal distribution; more specifically, for certain types of signal distribution SR is not observed [Das A, Stocks NG, Nikitin A, Hines EL. Quantifying stochastic resonance in a single threshold detector for random aperiodic signals. Fluctuation Noise Lett 2004;4:L247–65]. Here we show that suprathreshold stochastic resonance (SSR) – a novel and distinct form of SR – removes this limitation and hence leads to the conclusion that SSR can probably enhance the transmission of signals of any distribution and amplitude. SSR effects are studied in a parallel array of identical nonlinear threshold based devices. A double exponential signal distribution is chosen because this distribution did not demonstrate conventional SR effects in a single threshold device [Das A, Stocks NG, Nikitin A., Hines EL. Quantifying Stochastic resonance in a single threshold detector for random aperiodic signals. Fluctuation and Noise Letters 2004;4:L247-L265.]. SSR as a possible mechanism for enhancing transmission of speech signals in the human ear is also discussed. 2007 Elsevier B.V. All rights reserved. PACS: 02.50.Fz; 05.10. a

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The application of suprathreshold stochastic resonance to cochlear implant coding

In this paper we explore the possibility of using a recently discovered form of stochastic resonance termed suprathreshold stochastic resonance to improve speech comprehension in patients fitted with cochlear implants. A leaky-integrate-and-fire (LIF) neurone is used to model cochlear nerve activity when subject to electrical stimulation. This model, in principle, captures key aspects of tempor...

متن کامل

Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance.

Suprathreshold stochastic resonance (SSR) is a form of noise-enhanced signal transmission that occurs in a parallel array of independently noisy identical threshold nonlinearities, including model neurons. Unlike most forms of stochastic resonance, the output response to suprathreshold random input signals of arbitrary magnitude is improved by the presence of even small amounts of noise. In thi...

متن کامل

Design and performance analysis of a signal detector based on suprathreshold stochastic resonance

This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distr...

متن کامل

Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance

We examine the optimal threshold distribution in populations of noisy threshold devices. When the noise on each threshold is independent, and sufficiently large, the optimal thresholds are realized by the suprathreshold stochastic resonance effect, in which case all threshold devices are identical. This result has relevance for neural population coding, as such noisy threshold devices model the...

متن کامل

Smart sensor motion detection schemes in a noisy environment

Several motion detection schemes are considered and their responses to noisy signals investigated. The detection schemes include the Reichardt correlation detector, shunting inhibition neuron and the Horridge template model. These schemes are directionally selective and independent to the change in contrast. They essentially function by using spatial information and comparing it at successive t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016