Ying Zhang¹, Wei Li^1,*, Guidong Yang¹, Snezana Kirin²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2177-2199, 2024, DOI:10.32604/cmes.2023.030728 - 15 December 2023

Abstract The Mean First-Passage Time (MFPT) and Stochastic Resonance (SR) of a stochastic tumor-immune model with noise perturbation are discussed in this paper. Firstly, considering environmental perturbation, Gaussian white noise and Gaussian colored noise are introduced into a tumor growth model under immune surveillance. As follows, the long-time evolution of the tumor characterized by the Stationary Probability Density (SPD) and MFPT is obtained in theory on the basis of the Approximated Fokker-Planck Equation (AFPE). Herein the recurrence of the tumor from the extinction state to the tumor-present state is more concerned in this paper. A more… More >

Xiaoping Zhao^{1, 4}, Yifei Wang^{2, *}, Yonghong Zhang², Jiaxin Wu¹, Yunqing Shi³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 571-587, 2020, DOI:10.32604/cmc.2020.06363 - 08 April 2019

Abstract Stochastic resonance can use noise to enhance weak signals, effectively reducing the effect of noise signals on feature extraction. In order to improve the early fault recognition rate of rolling bearings, and to overcome the shortcomings of lack of interaction in the selection of SR (Stochastic Resonance) method parameters and the lack of validation of the extracted features, an adaptive genetic random resonance early fault diagnosis method for rolling bearings was proposed. compared with the existing methods, the AGSR (Adaptive Genetic Stochastic Resonance) method uses genetic algorithms to optimize the system parameters, and further optimizes More >

S. Deivalakshmi^*, P. Palanisamy¹, X. Z. Gao²

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 459-471, 2019, DOI:10.31209/2018.100000001

Abstract The main aim of this paper is to propose a new technique for enhancing the contrast of dark images using Dynamic Stochastic Resonance (DSR) and Multi Wavelet Transform (MWT), which is computationally more efficient than the conventional methods. In the work, for enhancing the contrast of dark images, the intrinsic noise (darkness) of dark images has been used. The proposed MWT-based DSR scheme (MWT-DSR) can yield better performances in terms of visual information and color preservation than already reported techniques. The desired output response is validated by the Relative Contrast Enhancement Factor (F), Perceptual Quality More >

Bohou Xu¹, Yibing Yang¹, Zhong-Ping Jiang², Daniel W. Repperger³

CMES-Computer Modeling in Engineering & Sciences, Vol.57, No.2, pp. 159-174, 2010, DOI:10.3970/cmes.2010.057.159

Abstract A modified two-dimensional parameter-induced stochastic resonance (2D-PSR) system is proposed. Both theoretical and simulation results indicate that the 2D-PSR system performs a resonant-like behavior when system parameters are properly adjusted. When applied to degraded image processing, 2D-PSR technique is proved to be able to attain higher SNR gain than traditional linear filters. Due to its strong robustness to environmental changes, adaptability, and complementarities with other methods, the proposed 2D-PSR technique turns out to be promising in the field of image processing. More >

Bohou Xu¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.4, pp. 97-98, 2009, DOI:10.3970/icces.2009.011.097

Abstract Stochastic resonance is a mechanical concept and may be used to image processing. This paper aims to develop an elementary theory of two-dimensional parameter-induced stochastic resonance (PSR) in order to contribute a new approach to nonlinear image processing. For tackling applications of stochastic resonance (SR) in image processing where adding noise may not be an easy task, we propose to generalize the concept of parameter-induced stochastic resonance from the one-dimensional case to the two-dimensional case. Specially, a novel two-dimensional system which demonstrates the feature of parameter-induced stochastic resonance is proposed for nonlinear image processing. An… More >