scholarly journals Recent Trends of Controlling Chaotic Resonance and Future Perspectives

2021 ◽  
Vol 7 ◽  
Author(s):  
Sou Nobukawa ◽  
Haruhiko Nishimura ◽  
Nobuhiko Wagatsuma ◽  
Keiichiro Inagaki ◽  
Teruya Yamanishi ◽  
...  
Keyword(s):  
Stochastic Resonance ◽  
Deterministic Chaos ◽  
Stochastic Noise ◽  
World Systems ◽  
Engineering Applications ◽  
Input Signals ◽  
Recent Trends ◽  
Signal Response ◽  
Emergence Of Chaos ◽  
Influence Of Noise

Stochastic resonance is a phenomenon in which the effects of additive noise strengthen the signal response against weak input signals in non-linear systems with a specific barrier or threshold. Recently, several studies on stochastic resonance have been conducted considering various engineering applications. In addition to additive stochastic noise, deterministic chaos causes a phenomenon similar to the stochastic resonance, which is known as chaotic resonance. The signal response of the chaotic resonance is maximized around the attractor-merging bifurcation for the emergence of chaos-chaos intermittency. Previous studies have shown that the sensitivity of chaotic resonance is higher than that of stochastic resonance. However, the engineering applications of chaotic resonance are limited. There are two possible reasons for this. First, the stochastic noise required to induce stochastic resonance can be easily controlled from outside of the stochastic resonance system. Conversely, in chaotic resonance, the attractor-merging bifurcation must be induced via the adjustment of internal system parameters. In many cases, achieving this adjustment from outside the system is difficult, particularly in biological systems. Second, chaotic resonance degrades owing to the influence of noise, which is generally inevitable in real-world systems. Herein, we introduce the findings of previous studies concerning chaotic resonance over the past decade and summarize the recent findings and conceivable approaches for the reduced region of orbit feedback method to address the aforementioned difficulties.

SUPPRESSION OF JAMMING IN EXCITABLE SYSTEMS BY APERIODIC STOCHASTIC RESONANCE

2004 ◽  
Vol 14 (10) ◽  
pp. 3519-3539 ◽  
Author(s):  
YING-CHENG LAI ◽  
ZONGHUA LIU ◽  
ARJE NACHMAN ◽  
LIQIANG ZHU
Keyword(s):  
Dynamical Systems ◽  
Stochastic Resonance ◽  
Narrow Band ◽  
Broad Band ◽  
Effective Mechanism ◽  
Strong Broad Band ◽  
Chaotic Signals ◽  
Input Signals ◽  
Excitable Systems ◽  
Processing Information

To suppress undesirable noise (jamming) associated with signals is important for many applications. Here we explore the idea of jamming suppression with realistic, aperiodic signals by stochastic resonance. In particular, we consider weak amplitude-modulated (AM), frequency-modulated (FM), and chaotic signals with strong, broad-band or narrow-band jamming, and show that aperiodic stochastic resonance occurring in an array of excitable dynamical systems can be effective to counter jamming. We provide formulas for quantitative measures characterizing the resonance. As excitability is ubiquitous in biological systems, our work suggests that aperiodic stochastic resonance may be a universal and effective mechanism for reducing noise associated with input signals for transmitting and processing information.

SIGNAL TRANSFER AND STOCHASTIC RESONANCE IN COUPLED NONLINEAR SYSTEMS

1999 ◽  
Vol 09 (06) ◽  
pp. 1159-1167 ◽  
Author(s):  
C. HAUPTMANN ◽  
F. KAISER ◽  
C. EICHWALD
Keyword(s):  
Stochastic Resonance ◽  
Harmonic Signal ◽  
Signal Transfer ◽  
Coherent Noise ◽  
Noise Sources ◽  
Bistable Systems ◽  
Coupled Nonlinear Oscillators ◽  
Initial Stage ◽  
Combined Action ◽  
Influence Of Noise

A model of coupled nonlinear oscillators is discussed, wherein Langevin-type bistable systems are combined with self-sustained oscillators. An external harmonic signal is coupled in a subthreshold manner into the bistable systems at the initial stage of the signal chain. Signal transfer through the oscillators is studied under the influence of noise. Different noise contributions, including spatially-incoherent and spatially-coherent noise sources are considered. Results reveal a stochastic resonance kind of behavior at different stages of the signal transfer, specifically the harmonic signal is transduced through the whole system of coupled oscillators. The combined action of spatially-incoherent and spatially-coherent noise exhibits constructive as well as destructive influences on signal amplification.

Noise Induced Order: Stochastic Resonance

1998 ◽  
Vol 08 (05) ◽  
pp. 869-879 ◽  
Author(s):  
Lutz Schimansky-Geier ◽  
Jan A. Freund ◽  
Alexander B. Neiman ◽  
Boris Shulgin
Keyword(s):  
Information Theory ◽  
Stochastic Resonance ◽  
Noise Intensity ◽  
Electronic Circuit ◽  
Schmitt Trigger ◽  
Periodic Component ◽  
Large Signal ◽  
Input Signals

We investigate stochastic resonance in the framework of information theory. Input signals are taken from an electronic circuit and output signals are produced by a Schmitt trigger. These electronic signals are analyzed with respect to their informational contents. Conditional entropies and Kullback measures exhibit extrema for values of noise intensity in the range of stochastic resonance. However, it has to be noted that these extrema are related to synchronization effects, observed in stochastic resonance for large signal amplitudes, rather than to a peak in the related spectrum indicating some periodic component.

Enhancement of weak-signal response based on stochastic resonance in carbon nanotube field-effect transistors

2010 ◽  
Vol 108 (10) ◽  
pp. 104313 ◽  
Author(s):  
Yasufumi Hakamata ◽  
Yasuhide Ohno ◽  
Kenzo Maehashi ◽  
Seiya Kasai ◽  
Koichi Inoue ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Stochastic Resonance ◽  
Field Effect ◽  
Field Effect Transistors ◽  
Weak Signal ◽  
Signal Response

On the stochastic resonance phenomenon in parametrically excited systems

2018 ◽  
Vol 30 (5) ◽  
pp. 986-1003 ◽  
Author(s):  
VLADISLAV SOROKIN ◽  
ILIYA BLEKHMAN
Keyword(s):  
Stochastic Resonance ◽  
High Frequency ◽  
Stochastic Systems ◽  
Resonance Phenomenon ◽  
Deterministic Approach ◽  
Parametrically Excited ◽  
System Behaviour ◽  
Input Signals ◽  
Mass Properties ◽  
Stochastic Resonance Phenomenon

The stochastic resonance phenomenon implies “positive” changing of a system behaviour when noise is added to the system. The phenomenon has found numerous applications in physics, neuroscience, biology, medicine, mechanics and other fields. The present paper concerns this phenomenon for parametrically excited stochastic systems, i.e. systems that feature deterministic input signals that affect their parameters, e.g. stiffness, damping or mass properties. Parametrically excited systems are now widely used for signal sensing, filtering and amplification, particularly in micro- and nanoscale applications. And noise and uncertainty can be essential for systems at this scale. Thus, these systems potentially can exhibit stochastic resonance. In the present paper, we use a “deterministic” approach to describe the stochastic resonance phenomenon that implies replacing noise by deterministic high-frequency excitations. By means of the approach, we show that stochastic resonance can occur for parametrically excited systems and determine the corresponding resonance conditions.

scholarly journals Adaptive stochastic resonance for unknown and variable input signals

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Patrick Krauss ◽  
Claus Metzner ◽  
Achim Schilling ◽  
Christian Schütz ◽  
Konstantin Tziridis ◽  
...  
Keyword(s):  
Stochastic Resonance ◽  
Input Signals

A CHARACTERIZATION OF SUPRATHRESHOLD STOCHASTIC RESONANCE IN AN ARRAY OF COMPARATORS BY CORRELATION COEFFICIENT

2002 ◽  
Vol 02 (03) ◽  
pp. L205-L220 ◽  
Author(s):  
MARK D. MCDONNELL ◽  
DEREK ABBOTT ◽  
CHARLES E. M. PEARCE
Keyword(s):  
Correlation Coefficient ◽  
Stochastic Resonance ◽  
Output Signal ◽  
Quantization Noise ◽  
Alternative Measure ◽  
Neuron Models ◽  
Input Noise ◽  
Input Signals ◽  
Output Noise ◽  
Suprathreshold Stochastic Resonance

Suprathreshold Stochastic Resonance (SSR), as described recently by Stocks, is a new form of Stochastic Resonance (SR) which occurs in arrays of nonlinear elements subject to aperiodic input signals and noise. These array elements can be threshold devices or FitzHugh-Nagumo neuron models for example. The distinguishing feature of SSR is that the output measure of interest is not maximized simply for nonzero values of input noise, but is maximized for nonzero values of the input noise to signal intensity ratio, and the effect occurs for signals of arbitrary magnitude and not just subthreshold signals. The original papers described SSR in terms of information theory. Previous work on SR has used correlation based measures to quantify SR for aperiodic input signals. Here, we argue the validity of correlation based measures and derive exact expressions for the cross-correlation coefficient in the same system as the original work, and show that the SSR effect also occurs in this alternative measure. If the output signal is thought of as a digital estimate of the input signal, then the output noise can be considered simply as quantization noise. We therefore derive an expression for the output signal to quantization noise ratio, and show that SSR also occurs in this measure.

STOCHASTIC RESONANCE IN COUPLED THRESHOLD ELEMENTS WITH INPUT SIGNALS SHIFTED IN PHASE

2000 ◽  
Vol 14 (08) ◽  
pp. 837-852
Author(s):  
A. KRAWIECKI ◽  
A. SUKIENNICKI ◽  
R. A. KOSIŃSKI
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stochastic Resonance ◽  
Response Function ◽  
Signal To Noise Ratio ◽  
Binary Response ◽  
Signal To Noise ◽  
Input And Output ◽  
Input Signals ◽  
Periodic Signals

Stochastic resonance in a system of two coupled threshold elements (neurons) forming a small artificial neural network is investigated. The elements have either antisymmetric or logistic (binary) response function and are driven by periodic signals and independent noises. Periodic signals at their inputs have equal amplitudes and frequencies but are shifted in phase. Depending on the response function and the phase shift, enhancement of stochastic resonance in individual elements, characterized by the output signal-to-noise ratio, and stochastic resonance with a spatiotemporal input signal, characterized by the correlation function between the input and output signals, are observed for proper coupling between elements.

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