in current years, the application of biopotential signals has received a lot of attention in literature. one of these signals is an electromyogram (emg) generated by active muscles. surface emg (semg) signal is recorded over the skin, as the representative of the muscle activity. since its amplitude can be as low as 50 µv, it is sensitive to undesirable noise signals such as power‑line interfer...

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is propos...

Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...

the importance as well as the difficulty of the problem of ranking fuzzy numbers is pointed out. here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its signal/noise ratios, where the signal and the noise are defined as the middle-point and the spread of each $gamma$-cut of a fuzzy number, respectively. we use the va...

-----------------------------------------------------------------------------ABSTRACT------------------------------------------------------Independent Component Analysis (ICA) is the decomposition technique of a random vector of data into linear components which are “independent as possible.” Involves finding a suitable representation of multivariate data for computational and conceptual simpli...

The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...