Umashankar Ganesan^1,*, A. Vimala Juliet², R. Amala Jenith Joshi³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.033759 - 15 March 2023

Abstract Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD).… 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 >

C.V. Nastos, T.C. Theodosiou, C.S. Rekatsinas, D.A. Saravanos¹

CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.5, pp. 379-409, 2015, DOI:10.3970/cmes.2015.107.379

Abstract A computationally efficient numerical method is developed for the prediction of transient response in orthotropic rod and beam structures. The method takes advantage of the outstanding properties of compactly supported Daubechies wavelet scaling functions for the spatial approximation of displacements in a finite domain of the structure, hence is termed Finite Wavelet Domain (FWD) method. The basic principles and advantages of the method are presented and the discretization of the equations of motion is formulated for one-dimensional structures. Numerical results for the simulation of propagating guided waves in rods and strips are presented and compared More >

Yanan Liu¹, Yinghua liu¹, Zhangzhi Cen¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.3, No.3, pp. 139-144, 2007, DOI:10.3970/icces.2007.003.139

Abstract In this paper, a Daubechies(DB) wavelet-based meshless method is proposed to analyze 2-D elastoplasticity problems. Using DB wavelet scaling functions and wavelet functions as basis functions to approximate the unknown field functions, there is no need to construct the shape functions costly as done in FEM and conventional meshless methods. Incremental formulations are established for solution of 2-D elastoplasticity problems. In addition, the property of DB wavelet is used to make the method concise in formulations, flexible in applications and easy to realize. Due to the lack of Kroneker delta properties in scaling functions and More >