SIGNAL-TO-NOISE RATIO GAIN VIA CORRELATED NOISE IN AN ENSEMBLE OF NOISY NEURONS

2020 ◽  
Vol 28 (01) ◽  
pp. 111-126
Author(s):  
TIANQUAN FENG
Keyword(s):  
Signal To Noise Ratio ◽  
Internal Noise ◽  
Linear Response Theory ◽  
Periodic Signal ◽  
Correlated Noise ◽  
Signal To Noise ◽  
Optimal Value ◽  
Nonlinear Amplification ◽  
Noise Ratio ◽  
Snr Gain

The collective response of an ensemble of leaky integrate-and-fire neurons induced by local correlated noise is investigated theoretically. Based on the linear response theory, we derive the analytic expression of signal-to-noise ratio (SNR). Numerical results show that the amplitude of internal noise can be increased up to an optimal value where the output SNR reaches a maximum value. Interestingly, we find that the correlated noise between the nearest neurons could lead to the obvious SNR gain. We also show that the SNR can reach unity under condition that the correlated noise between the nearest neurons is negative. This nonlinear amplification of SNR gain in an ensemble of noisy neurons can be related to the array stochastic resonance (SR) phenomenon. Furthermore, we also show that the SNR gain can also be optimized by tuning the number of neuron units, frequency and amplitude of the weak periodic signal.

scholarly journals Stochastic resonance in periodically driven bistable systems subjected to anomalous diffusion

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
F. Naha Nzoupe ◽  
Alain M. Dikandé
Keyword(s):  
Stochastic Resonance ◽  
Signal To Noise Ratio ◽  
Planck Equation ◽  
Relevant Information ◽  
Periodic Signal ◽  
Signal To Noise ◽  
Periodically Driven ◽  
Loop Area ◽  
Bistable Systems ◽  
Noise Ratio

AbstractThe occurrence of stochastic resonance in bistable systems undergoing anomalous diffusions, which arise from density-dependent fluctuations, is investigated with an emphasis on the analytical formulation of the problem as well as a possible analytical derivation of key quantifiers of stochastic resonance. The nonlinear Fokker–Planck equation describing the system dynamics, together with the corresponding Ito–Langevin equation, is formulated. In the linear response regime, analytical expressions of the spectral amplification, of the signal-to-noise ratio and of the hysteresis loop area are derived as quantifiers of stochastic resonance. These quantifiers are found to be strongly dependent on the parameters controlling the type of diffusion; in particular, the peak characterizing the signal-to-noise ratio occurs only in close ranges of parameters. Results introduce the relevant information that, taking into consideration the interactions of anomalous diffusive systems with a periodic signal, can provide a better understanding of the physics of stochastic resonance in bistable systems driven by periodic forces.

scholarly journals Improvement of signal-to-noise ratio in parallel neuron arrays with spatially nearest neighbor correlated noise

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0200890
Author(s):  
Tianquan Feng ◽  
Qingrong Chen ◽  
Ming Yi ◽  
Zhongdang Xiao
Keyword(s):  
Nearest Neighbor ◽  
Signal To Noise Ratio ◽  
Correlated Noise ◽  
Signal To Noise ◽  
Noise Ratio

SIGNAL-TO-NOISE RATIO GAIN IN NON-DYNAMICAL AND DYNAMICAL BISTABLE STOCHASTIC RESONATORS

2002 ◽  
Vol 02 (03) ◽  
pp. L147-L155 ◽  
Author(s):  
PETER MAKRA ◽  
ZOLTAN GINGL ◽  
LASZLO B. KISH
Keyword(s):  
Stochastic Resonance ◽  
Signal To Noise Ratio ◽  
Schmitt Trigger ◽  
Total Power ◽  
Signal To Noise ◽  
Simulation Techniques ◽  
Duty Cycles ◽  
Signal Simulation ◽  
Noise Ratio ◽  
Snr Gain

It has recently been reported that in some systems showing stochastic resonance, the signal-to-noise ratio (SNR) at the output can significantly exceed that at the input; in other words, SNR gain is possible. We took two such systems, the non-dynamical Schmitt trigger and the dynamical double wellpotential, and using numerical and mixed-signal simulation techniques, we examined what SNR gains these systems can provide. In the non-linear response limit, we obtained SNR gains much greater than unity for both systems. In addition to the classical narrow-band SNR definition, we also measured the ratio of the total power of the signal to the power of the noise part, and it showed even better signal improvement. Here we present a brief review of our results, and scrutinise, for both the Schmitt-trigger and the double well potential, the behaviour of the SNR gain by stochastic resonance for different signal amplitudes and duty cycles. We also discuss the mechanism of providing gains greater than unity.

Study on the SNR Gain of RAKE Demodulator

2014 ◽  
Vol 971-973 ◽  
pp. 755-759
Author(s):  
Chu Rong Zhu ◽  
Hai Yang Fu ◽  
Xiang Dong Jia
Keyword(s):  
Performance Evaluation ◽  
Closed Form ◽  
Signal To Noise Ratio ◽  
Evaluation Methods ◽  
Signal To Noise ◽  
Diversity Reception ◽  
Noise Ratio ◽  
Snr Gain

Classic RAKE demodulator(RAKEDE), multi-carrier coherent RAKEDE and RAKEDE with two antennas are given in the paper. According to those schemes provided, the GSNR, which means the gain of signal to noise ratio (SNR), for those three kinds of RAKEDE is derived, and the closed form of the expression for GSNR of those three kinds of RAKEDE is given in the paper. Comparing with those performance evaluation methods of RAKEDE existed, the method derived in this paper on the basis of diversity reception is more usable and easy to be accept.

Stochastic Resonance in a Time-Delayed Logistic Growth Model Driven by Periodic Signal and White Noise

2011 ◽  
Vol 117-119 ◽  
pp. 703-707
Author(s):  
Yu Rong Zhou ◽  
Chong Qiu Fang
Keyword(s):  
White Noise ◽  
Stochastic Resonance ◽  
Growth Model ◽  
Delay Time ◽  
Signal To Noise Ratio ◽  
Logistic Growth ◽  
Periodic Signal ◽  
Signal To Noise ◽  
Logistic Growth Model ◽  
Noise Ratio

stochastic resonance; time-delayed Logistic growth model; signal-to-noise ratio Abstract. The stochastic resonance in a time-delayed Logistic growth model subject to correlated multiplicative and additive white noise as well as to multiplicative periodic signal is investigated. Using small time delay approximation, we get the expression of the signal-to-noise ratio (SNR). It is found that the SNR is a non-monotonic function of the system parameters, of the intensities of the multiplicative and additive noise, as well as of the correlation strength between the two noises. The effects of the delay time in the random force is in opposition to that of the delay time in the deterministic force.

NOISE IMPROVEMENTS IN STOCHASTIC RESONANCE: FROM SIGNAL AMPLIFICATION TO OPTIMAL DETECTION

2002 ◽  
Vol 02 (03) ◽  
pp. L221-L233 ◽  
Author(s):  
FRANÇOIS CHAPEAU-BLONDEAU ◽  
DAVID ROUSSEAU
Keyword(s):  
Stochastic Resonance ◽  
Signal Amplification ◽  
Signal To Noise Ratio ◽  
Periodic Signal ◽  
Optimal Detection ◽  
Input Output ◽  
Signal To Noise ◽  
Optimal Processing ◽  
Noise Ratio ◽  
Noise Benefits

It is demonstrated that benefits from the noise can be gained at various levels in stochastic resonance. Raising the noise can produce signal amplification as well as signal-to-noise ratio improvement, input–output gain exceeding unity in signal-to-noise ratio, and enhanced performance in optimal processing. This series of benefits is successively exhibited in the processing of a periodic signal coupled to a white noise through essentially static nonlinearities. Especially, it is established that noise benefits in stochastic resonance can extend up to optimal processing, by considering an optimal Bayesian detector whose performance is improvable by raising the level of the noise.

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