Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …

Signal decomposition is an effective tool to assist identification of modal information in time-
domain signals. Two signal decomposition methods, including the empirical wavelet …

In this paper, a new method has been presented for the time–frequency (TF) representation
of non-stationary signals. The existing empirical wavelet transform (EWT) has been …

Parkinson's disease (PD) can cause many non-motor and motor symptoms such as speech
and smell. One of the difficulties that Parkinson's patients can experience is a change in …

Respiration rate (RR) and heartbeat rate (HR) are important physiological parameters for a
person. Impulse radio ultra-wideband (IR-UWB) is a promising technology for non-contact …

This paper presents an automated seizure detection method based on variational mode
decomposition (VMD). In VMD, the number of decomposed modes K and the penalty …

The stock market plays a vital role in the economic and social organization of many
countries. Since stock price time series are highly noisy, nonparametric, volatility …

Variational mode decomposition (VMD) with a non-recursive and narrow-band filtering
nature is a promising time-frequency analysis tool, which can deal effectively with a non …

The development of advanced technologies based on computer aid models in the domain of
crops and agriculture productively is a modern advancement. Machine learning (ML) based …

Lung disease encompasses various disorders that result in impaired lung function and
breathing difficulties. We propose a two-stage pipeline for automated lung disease detection …