Wavelet transform provides a fine means of classifying seizure EEG signals from the normal EEG signals. Stationary wavelet transform (SWT) is used to further improve the performance of discrete wavelet transform. EEG signal prediction and classification can be bolstered up by applying SWT. In this work the residues obtained from denoising the signal using SWT is considered. Its arithmetical fac...

BACKGROUND Postural balance is vital for safely carrying out many daily activities, such as locomotion. The purpose of this study was to determine how changes in normal standing (NS) and standing with toe-extension (SWT) impact postural control during quiet standing. Furthermore, the research aimed to examine the extent to which the effect of these factors differed between genders. METHODOLOG...

Idiopathic Parkinson's disease (PD) is often accompanied by a pattern of executive deficits similar to those found in patients with frontal lobe lesions. We investigated whether such cognitive deficits are attributable to frontal lobe dysfunction as a direct consequence of impaired mesocortical dopaminergic transmission or an indirect consequence of impaired nigrostriatal dopaminergic function....

Super resolution is the process of reconstructing high resolution(HR) image from multiple low resolution(LR) images of a scene . LR images are at a specific pixel shift from each other. High Resolution(HR) grids are formed from these LR images using Stationary Wavelet Transform (SWT) by image registration. Interpolation of the missing pixel in the HR grid is done using Curvelet Transform(CT). E...

Previous direct measurements of left ventricular systolic wall thickening (SWT) in animal studies have yielded values approximately one-half those found echocardiographically in humans, suggesting a possible overestimation of SWT by echocardiographic techniques. To test the validity of echocardiographic SWT measurements, the relationship between echocardiographically determined end-diastolic an...

Image fusion is a process of combining relevant information from two or more images from different sensors based on certain algorithm. Many algorithms have been proposed for pixel level image fusion. In this paper, Empirical Mode Decomposition is the recent, powerful tool for adaptive multi scale analysis of non stationary signals that decomposes them into Intrinsic Mode Functions (IMFs). Hence...

Network-based intrusion has become a serious threat to today’s highly networked information systems, yet the overwhelming majority of current network security mechanisms are “passive” in response to network-based attacks. In particular, tracing and detection of the source of network-based intrusion has been left largely untouched in existing intrusion detection mechanisms. The fact that intrude...

OBJECTIVES The aim of this paper is to introduce and test a general, wavelet-based method for the automatic removal of noise and artefact from psychophysiological data. METHODS Statistical wavelet thresholding (SWT) performs blind source separation by transforming data to the wavelet domain, and subsequent filtering of wavelet coefficients based on a statistical framework. The observed wavele...