Use Of Stochastic Resonance Research Articles

Subthreshold Vibration Influences Standing Balance but Has Unclear Impact on Somatosensation in Persons With Transtibial Amputations.

Stochastic resonance has been successfully used to improve human movement when using subthreshold vibration. Recent work has shown promise in improving mobility in individuals with unilateral lower limb amputations. Furthering this work, we present an investigation of two different signal structures in the use of stochastic resonance to improve mobility in individuals with unilateral lower limb amputations. Cutaneous somatosensation and standing balance measures using spatial and temporal analysis were assessed. There were no differences in the somatosensation measures, but differences in the temporal characteristics of the standing measures were seen with the various vibration structures when compared to no vibration, one of which suggesting mass may play an important role in determining who may or may not benefit from this intervention. Stochastic resonance employed with subthreshold vibration influences mobility in individuals with unilateral amputations, but the full direction and extent of influence is yet to be understood.

Stochastic Resonance with Dynamic Compression Improves the Growth of Adult Chondrocytes in Agarose Gel Constructs.

Dynamic mechanical stimulation has been an effective method to improve the growth of tissue engineering cartilage constructs derived from immature cells. However, when more mature cell populations are used, results are often variable due to the differing responses of these cells to external stimuli. This can be especially detrimental in the case of mechanical loading. In previous studies, multi-modal mechanical stimulation in the form of stochastic resonance was shown to be effective at improving the growth of young bovine chondrocytes. Thus, the aim of this study was to investigate the short-term and long-term effects of stochastic resonance on two groups of bovine chondrocytes, adult (> 30month) and juvenile (~ 18months). While the juvenile cells outperformed the adult cells in terms of their anabolic response to loading, combined mechanical loading for both age groups resulted in greater matrix synthesis compared to compressive loading alone. In the adult cells, potential pathological tissue formation was evident with the presence of cell clustering. However, the presence of broad-band mechanical vibrations (alone or with compressive loading) appeared to mitigate this response and allow these cells to attain a growth response similar to the juvenile, unstimulated cells. Therefore, the use of stochastic resonance appears to show promise as a method to improve the formation and properties of tissue engineered cartilage constructs, irrespective of cell age.

Impact of the Stochastic Resonance on Dark and Illumination Variant Images for Face Detection

This paper associates the impact of the stochastic resonance for detecting the presence of face on dark and illumination variant images. It is quite difficult to detect the faces from the images taken in a dark environment and under different illumination variant conditions due to the unclear visibility of the image. In this paper, we have designed an algorithm by combining the stochastic resonance along with our high performance face detector presented previously. We have developed “our SR for image processing” for the enhancement of the image, which extracts the image candidates from the dark and illumination variant images and make them visible. The Gaussian white noise is applied to the dark image keeping the threshold value at zero constant. The resultant images are then summed up in a series for extracting the image candidates from the dark images and for making them visible. This technique has been developed from the summing network process of the stochastic resonance noise. The images once enhanced and made visible is applied to our face detector for detecting the presence of the face in an image. The idea of our SR technique for image processing and the use of stochastic resonance in a face detection algorithm for the static dark images clearly reflects the novelty of our paper. We performed various experiments on various dark and illumination variant images to confirm the effectiveness of our current research.

Enhanced vibrational energy harvesting using nonlinear stochastic resonance

Stochastic resonance has seen wide application in the physical sciences as a tool to understand weak signal amplification by noise. However, this apparently counter-intuitive phenomenon does not appear to have been exploited as a tool to enhance vibrational energy harvesting. In this note we demonstrate that by adding periodic forcing to a vibrationally excited energy harvesting mechanism, the power available from the device is apparently enhanced over a mechanism without periodic forcing. In order to illustrate this novel effect, a conceptually simple, but plausible model of such a device is proposed to explore the use of stochastic resonance to enhance vibrational energy harvesting.

Detection of B-FSK signals using schmidt trigger

Possibility to record B-FSK signals with use of stochastic resonance is studied. A Schmidt trigger is employed as bistable stochastic resonator. A digital model of the detector is proposed and quantitative results are obtained by means of simulations. Dependence of the probability of correctly detected bits on the added noise power and on the low-pass filter cutoff frequency is studied. Also the stability of the detector with respect to channel-introduced phase shifts is revealed.

A study of a mathematical model of electrogastrography by use of stochastic resonance

A study of a mathematical model of electrogastrography by use of stochastic resonance

Constructive action of noise for impulsive noise removal in scalar images

A nonlinear variational approach to remove impulsive noise in scalar images is proposed. Taking benefit from recent studies on the use of stochastic resonance and the constructive role of noise in nonlinear processes, the process is based on the classical restoration process of Perona-Malik in which a Gaussian noise is purposely injected. It is shown that this new process can outperform the original restoration process of Perona-Malik.

Use of stochastic resonance for enhancement of low-level vibration signal components

The increase in certain aspects of non-linear system output with the addition of noise to the system input is called stochastic resonance. The possibility of producing and using stochastic resonance to enhance low-level components of signals was investigated. Both a two-component model signal and actual vibration signals were used. The signal analysis system constructed consisted of a multi-component signal, a random or noise component added to the signal and a threshold for signal recognition. The parts of the noise plus original signal augmented signal that exceeded a threshold formed a new signal that was characterised in terms of the magnitudes of signal components. The effects of added noise level on the new signal were ascertained. Stochastic resonance was demonstrated as enhancement of low-level components of the model and actual vibration signals with the effect being dependent on the level of added noise.

On the use of stochastic resonance in sine detection

This paper deals with the use of stochastic resonance (SR) for detection purposes. The nonlinear physical phenomenon of SR generally occurs in dynamical bistable systems excited by a noisy sine: such systems are able to force cooperation between sine and noise such that the noise amplifies the sine. Because of this non-intuitive effect, the use of SR can be envisaged to detect small amplitude sines corrupted by additive noise. In this paper we recall some basics of detection and then show why SR can be used in sine detection context. After recalling some basics of SR in discrete time, we show how to use SR in a detection scheme.

Behavioral stochastic resonance: how a noisy army betrays its outpost.

Juvenile paddlefish prey upon single zooplankton by detecting a weak electric signature resulting from its feeding and swimming motions. Moreover, it has recently been shown that paddlefish make use of stochastic resonance near the threshold for prey detection: a process termed behavioral stochastic resonance. But this process depends upon an external source of electric noise. A swarm of plankton, for example, Daphnia, can provide this noise. Assuming that juvenile paddlefish attack single Daphnia as outliers in the vicinity of the swarm, making use of noise from the swarm, we calculate the spatial distribution of the average phase locking period for the subthreshold signals acting at the paddlefish rostrum. Numeric evaluation of analytic formulas supports the notion of a noise-induced widening of the capture area quantitatively.

Stochastic resonance enhances the electrosensory information available to paddlefish for prey capture.

Recent behavior experiments have demonstrated that paddlefish can make use of stochastic resonance while feeding on Daphnia plankton. Here we calculate the information content of the noisy Daphnia signal at the paddlefish rostrum using an exact statistical treatment of threshold stochastic resonance as a minimal neural model. These calculations compare well with experimentally obtained data on paddlefish strikes at Daphnia prey.