Type Of Stochastic Resonance Research Articles

A stochastic resonance etection algorithm based on orthonormalized basis function for magnetic anomaly detection.

To address the problem that the performance of the detector in airborne magnetic anomaly detection (MAD) is terrible, a stochastic resonance (SR) detection algorithm based on orthonormalized basis function (OBF-SR) is proposed for MAD under low signal-to-noise ratio conditions. The signal contaminated by noise is first preprocessed by the OBF method, where the sum of the three components in the OBF space is selected as the SR system input. Then, a parallel SR system with different initial states is designed to detect the signal. Finally, the simulation analysis of MAD methods is performed to draw a comparison between the OBF-SR method, the typical SR method, and the OBF method. The results show that the OBF-SR method outperforms the SR and OBF methods in the detection probability and detection range under the same conditions.

Typical stochastic resonance models and their applications in steady-state visual evoked potential detection technology

Typical stochastic resonance models and their applications in steady-state visual evoked potential detection technology

Rotation-translation coupling of a double-headed Brownian motor in a traveling-wave potential

Considering a double-headed Brownian motor moving with both translational and rotational degrees of freedom, we investigate the directed transport properties of the system in a traveling-wave potential. It is found that the traveling wave provides the essential condition of the directed transport for the system, and at an appropriate angular frequency, the positive current can be optimized. A general current reversal appears by modulating the angular frequency of the traveling wave, noise intensity, external driving force and the rod length. By transforming the dynamical equation in traveling-wave potential into that in a tilted potential, the mechanism of current reversal is analyzed. For both cases of Gaussian and Levy noises, the currents show similar dependence on the parameters. Moreover, the current in the tilted potential shows a typical stochastic resonance effect. The external driving force has also a resonance-like effect on the current in the tilted potential. But the current in the traveling-wave potential exhibits the reverse behaviors of that in the tilted potential. Besides, the currents obviously depend on the stability index of the Levy noise under certain conditions.

Stochastic resonance induced weak signal enhancement over controllable potential-well asymmetry

A dynamical model submerged in two colored multiplicative and additive noises by colored cross-correlation is established to elaborate controllable asymmetric potential-well with depth-asymmetry and width-asymmetry. We deduce the approximate signal-to-noise ratio (SNR) as widely adopted indicator for quantifying stochastic resonance (SR) behavior in accordance with the two-state theory, where the largest SNR peaks are almost attained in the asymmetry case. Moreover, the non-monotonic resonance curves excited by the incremental multiplicative colored noise intensity show the typical SR phenomenon and the SNR peaks decline as the additive colored noise intensity increases, the SR behavior induced by multiplicative colored noise is different from that induced by varying additive one. Noteworthy, the self-correlation time of alternative noises are more effective for controlling SR than cross-correlation time of noises. More interestingly, the output SNR demonstrates double resonance peaks by varying the cross-correlation intensity from negative to positive, however, the two local optimal cross-correlation intensities are almost maintained constant as the increasing of additive noise intensity. Even the large asymmetric well-depth is always beneficial to the improvement of SNR in comparison with well-width asymmetry at the same situation, which is due to the much more energy harvesting from the noises.

Observation of stochastic resonance in a liquid-crystal light valve with optical feedback induced by colored noise in the driving voltage.

Stochastic resonance is a noise phenomenon that benefits applications such as pattern formation, neural systems, microelectromechanical systems, and image processing. This study experimentally clarifies that the orientation of the liquid crystal molecules was switched between two stable positions when stochastic resonance was induced by colored noises in a liquid crystal light valve with optical feedback. Ornstein-Uhlenbeck and dichotomous noises were used for colored noise, and the noise was applied to the drive voltage of the liquid crystal light valve. The signal-to-noise ratio was measured with respect to changes in the noise type, noise intensity, and autocorrelation time of the noise. It was found that typical stochastic resonance was observed with a noise autocorrelation time of approximately 20 ms or more for both noise types, and dichotomous noise further enhanced the stochastic resonance compared to the Ornstein-Uhlenbeck noise. This suggests that it is possible to maximize stochastic resonance in a liquid crystal light valve by optimizing the conditions of colored noise.

A typical stochastic resonance in Landau-type potential field

Considering the significant influence of the asymmetric structure of the one-dimensional potential field on the stochastic resonance (SR), the research is extended to the two-dimensional asymmetric potential field. The Brownian particles moving in the Landau-type potential field served as the research object. According to the linear response theory and probability flow method, the analytical formula for the spectrum power amplification (SPA) of the physical system concerning the driving frequency is derived. When the SPA is used as a measurement index, the theoretical analysis shows that an atypical SR phenomenon occurs in the system. The reason is that as the noise intensity increases, the response mode changes due to the asymmetric structure of the Landau-type potential field. Moreover, the linear responses and the SPA are inversely proportional to the driving frequency. The conclusions of the theoretical analysis are verified by numerical simulation. Finally, the Landau-type potential system is applied to the bearing fault signal detection. The experimental results show that the Landau-type potential system can effectively diagnose the faults of the inner and outer ring of the bearings, which proves the application value of the Landau-type potential system.

Hysteresis can grant fitness in stochastically varying environment.

Although the existence of multiple stable phenotypes of living organisms enables random switching between phenotypes as well as non-random history dependent switching called hysteresis, only random switching has been considered in prior experimental and theoretical models of adaptation to variable environments. This work considers the possibility that hysteresis may also evolve together with random phenotype switching to maximize population growth. In addition to allowing the possibility that switching rates between different phenotypes may depend not only on a continuous environmental input variable, but also on the phenotype itself, the present work considers an opportunity cost of the switching events. This opportunity cost arises as a result of a lag phase experimentally observed after phenotype switching and stochastic behavior of the environmental input. It is shown that stochastic environmental variation results in maximal asymptotic growth rate when organisms display hysteresis for sufficiently slowly varying environmental input. At the same time, sinusoidal input does not cause evolution of memory suggesting that the connection between the lag phase, stochastic environmental variation and evolution of hysteresis is a result of a stochastic resonance type phenomenon.

A MODEL OF HIPPOCAMPAL MEMORY BASED ON AN ADAPTIVE LEARNING RULE OF SYNAPSES

We constructed a neural network of the hippocampus and proposed an adaptive learning rule of synapses to simulate the storing and retrieving processes of memory in the hippocampus by a mechanism of resonance. The hippocampus network consists of CA1, CA3 and DG, in particular, CA1 is a storage of memory, which receives inputs from both EC through perforant path (PP) and CA3 through Schaffer collaterals (SC). The stimulated results showed that the memory trace was unable to be encoded in CA1 when only a single subthreshold signal from EC or CA3 was inputted, of which the main reason might be lack of the resonance of the two signals. We calculated signal-to-noise ratio (SNR) of the network, and found it reached a peak value at appropriate SC connection strength, indicating that a typical stochastic resonance phenomenon appeared in PP signal detection. The inputs from EC and CA3 were able to enhance the memory representation in CA1, although still incomplete. We used a learning rule to modify synaptic weights by which the network could learn an external pattern. The hippocampus network tended to be stable after sufficient evolution. Some CA1 neurons show synchronized firings which are used to represent memory and are clearer than observed memory traces before learning. The model and results provide a good guidance to our understanding of the mechanism of the hippocampus memory.

Chaotic Resonance in Forced Chua^|^apos;s Oscillators

Stochastic resonance (SR) is a phenomenon in which dynamic noise is effectively used to induce state transitions in a double-well potential system driven by subthreshold input signals. The noises are supplied to the system as an additional force. Recently, a phenomenon called “chaotic resonance” (CR) has been spotlighted in the literature. CR can be observed in chaotic systems that have multiple strange attractors and the ability to accept subthreshold input signals; i.e., such CR systems do not require any external noise source, unlike traditional SR systems. In this study, we employed Chua’s oscillator as a candidate CR system. The oscillator was driven by a sinusoidal voltage source providing subthreshold input signals. In a certain range of input signal frequencies, we observed chaotic state transitions between the two attractors, whereas no state transition between the attractors was observed in the remaining frequency range. These findings indicated that chaotic fluctuations assisted the state transition. Furthermore, we observed nonmonotonic CR characteristics (correlation value and signal-to-noise ratio between the input signal and the output signal) that corresponded to typical nonmonotonic SR curves.

Prolonged Stochastic Resonance in Single Ion Channel Recordings

Stochastic resonance refers to the improved signal transduction through a system due to the addition of noise to that system. By prolonged stochastic resonance, we refer to the continued enhancement of signal transduction beyond the typical stochastic resonance maximum with increasing input noise. We present evidence of this phenomenon from single Alamethicin ion channels. Identification of the single channel in the presence of voltage noise was accomplished by extracting the conductance of the system by simultaneous voltage and current recording. We determined that, when applying low levels of voltage noise, no more than a single ion channel conducted at any given time. Further, we provide evidence that the prolongation of stochastic resonance in this system is due to the mechanotransductive effects of Alamethicin ion channels. It is well known that Alamethicin channels respond to mechanical tension in the lipid bilayer [1,2]. By extracting the capacitance of the system (again, via simultaneous voltage and current recordings), we record changes in membrane area with respect to applied voltage noise. We find that increasing voltage noise yields larger capacitances due to expansion of the lipid bilayer via the converse flexoelectric effect [3]. This areal expansion induces tension on the ion channel, increasing its conductance and enhancing signal transduction through the system. We therefore find that applied voltage noise affects Alamethicin ion channels by two means: directly, via the channel's voltage-gated nature; and indirectly, through the converse flexoelectric effect. This two-fold effect of voltage noise on channel conductance prolongs the signal transduction enhancement with increasing noise, and thus prolongs the effect of stochastic resonance in the system.[1] Stava, et al., Lab on a Chip, in press.[2] Opsahl and Webb, Biophys. J. (1994).[3] Todrov, et al., J. Phys. Chem. (1994).

Average transient period for precession regimes in magnetic films with dynamic bistability

The average transient time of regular regimes corresponding to the dynamic bistability state is studied using analysis of uniform precession of magnetization of a thin magnetic film. The possibility of controlling the transient process parameter by an additional ac magnetic field in the form of a harmonic of noise signal is established. A new type of stochastic resonance is detected, which corresponds to the probability of high-amplitude precession and is manifested during a short noise action.

Stochastic resonance of magnetization precession regimes under conditions of dynamic bistability

An analysis of the magnetization precession regimes under conditions of dynamic bistability revealed a new type of stochastic resonance, which arises during the short-time action of a noise signal and is related to the probability of attaining one of the stable regimes. Features of this stochastic effect have been studied.

Stochastic resonance between the limiting cycles of precession dynamics

A new type of stochastic resonance that arises between two precession modes under dynamic bistability conditions and is excited by an alternating magnetic field, including a harmonic signal and a white noise, has been studied using a numerical analysis of the uniform magnetization precession in a thin film. The spectrum of the steady-state dynamics of the system at stochastic resonance has been investigated, and its distinctive features have been revealed for the longitudinal and transverse orientations of the additional alternating field.

Stochastic resonance in an overdamped harmonic oscillator

The stochastic resonance in an overdamped harmonic oscillator driven by cross-correlation Gaussian white noises in which one of the noises is modulated by a periodic signal is studied. By means of the Fourier transform of the stationary correlation function, an exact expression of the signal-to-noise ratio for the overdamped harmonic oscillator stochastic model is derived. Results reveal that there are two types of stochastic resonance in an overdamped harmonic oscillator stochastic model. One type of stochastic resonance is that a resonance peak exists in the curves of signal-to-noise ratio versus the multiplicative noise intensity Q. Another type of stochastic resonance is that a resonance peak exists in the curves of signal-to-noise ratio versus the oscillator frequency ω. By changing the value of signal frequency Ω, the signal-to-noise ratio versus Q curve can exhibit three different forms: the form with a signal peak, the form with a peak following a valley, and the monotonic form.

Stochastic quasi-momentum resonance in metallic superlattices

A new type of stochastic resonance excited by a longitudinal magnetic field (including a harmonic signal and noise) is studied using numerical analysis of the system of coupled magnetic moments of a multilayer metallic structure. The resonance is characterized by the phase of rest and the phase of statistical oscillations. The possibility of controlling the resonance by varying the static field, as well as the parameters of noise and the harmonic signal, is established.

Stochastic resonance in a single-mode laser driven by frequency modulated signal and coloured noises

By adding frequency modulated signals to the intensity equation of gain–noise model of the single-mode laser driven by two coloured noises which are correlated, this paper uses the linear approximation method to calculate the power spectrum and signal-to-noise ratio (SNR) of the laser intensity. The results show that the SNR appears typical stochastic resonance with the variation of intensity of the pump noise and quantum noise. As the amplitude of a modulated signal has effects on the SNR, it shows suppression, monotone increasing, stochastic resonance, and multiple stochastic resonance with the variation of the frequency of a carrier signal and modulated signal.

Effect of the period modulation of the correlation intensity between color noises on the stochastic resonance of the single-mode laser with the signal modulation

For the laser system in which the correlation intensity between color noises is modulated by the time period，we investigate the stochastic resonance with the signal modulation of the noise. By means of the linear approximation，we calculate the intensity correlation function and signal-to-noise ratio （SNR） and discuss the evolution of the SNR with the noise intensity and self-correlation time of noises and signal frequency and time period modulation frequency. A new stochastic resonance is found. The evolution of the signal-noise ratio with the time period modulation frequency reveals periodic oscillation. We obtain the generalized stochastic resonance, in which the evolution of the signal-noise ratio with the self-correlation time of the pump noises and signal frequency presents the stochastic resonance. The typical stochastic resonance of the signal-noise ratio with the noise intensity is obtained also. The evolution of the signal-noise ratio with the self-correlation time of the quantum noise shows the restrainment.

Stochastic resonance of frequency modulated signals in a linear model of single-mode laser

By adding frequency modulated signal to the equation of the laser intensity of the gain-noise model of the single-mode lasers, we use the linear approximation method to calculate the power spectrum and signal-to-noise ratio (SNR) of the laser intensity, which is driven by two white noises correlated in the form of δ function. The result shows that the SNR shows typical stochastic resonance with the change of intensities of the pump noise and quantum noise. As the amplitude of a modulated signal has an effect on the SNR， it shows suppression, monotonic increase, resonance, suppression and resonance and so on， with the varing of the frequencies of the carrier signal and modulated signal.

Optimal observability of sustained stochastic competitive inhibition oscillations at organellar volumes

When molecules are present in small numbers, such as is frequently the case in cells, the usual assumptions leading to differential rate equations are invalid and it is necessary to use a stochastic description which takes into account the randomness of reactive encounters in solution. We display a very simple biochemical model, ordinary competitive inhibition with substrate inflow, which is only capable of damped oscillations in the deterministic mass-action rate equation limit, but which displays sustained oscillations in stochastic simulations. We define an observability parameter, which is essentially just the ratio of the amplitude of the oscillations to the mean value of the concentration. A maximum in the observability is seen as the volume is varied, a phenomenon we name system-size observability resonance by analogy with other types of stochastic resonance. For the parameters of this study, the maximum in the observability occurs at volumes similar to those of bacterial cells or of eukaryotic organelles.

Statistical approaches for investigating silk properties

Amino acid repeats or motifs have engendered interest because of their significance for protein physical characteristics as well as folding properties. Spider dragline silk proteins are unique because they are composed of long repetitive sections and relatively short non-repetitive sections that are known to interact to generate the very peculiar mechanical and solubility properties of silk. Computational analysis compared with in vitro measurements suggest that the silks achieve their unique pattern of extreme solubility inside the spider glands/complete insolubility outside by correlating their repetitive hydrophobic regions through a type of stochastic resonance, generated by the addition of the non-repetitive sequences to a basically periodic hydrophobicity pattern.