This paper deals with the problem of extracting information from non-stationary signals in the
form of features that can be used for effective decision-making in both data analysis and …

This paper presents high-resolution multisensor time–frequency distributions (MTFDs) and
their applications to the analysis of multichannel non-stationary signals. The approach …

Time-frequency (TF) based machine learning methodologies can improve the design of
classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF …

In recent years, a wealth of research has emerged addressing various aspects of mobile
communications signal processing. New applications and services are continually arising …

Numerous indoor localization techniques have been proposed recently to meet the intensive
demand for location-based service (LBS). Among them, the most popular solutions are the …

This article presents a general methodology for processing non-stationary signals for the
purpose of classification and localization. The methodology combines methods adapted …

We propose an estimator for the Ricean K-factor which has applications in mobile
communication systems. The estimator is based on the statistics of the instantaneous …

In this paper, a new algorithm is proposed to estimate mobile speed for broadband wireless
communications, which often encounter large number of fading channel taps causing severe …

This paper presents an introduction to time-frequency (TF) methods in signal processing,
and a novel approach for EEG abnormalities detection and classification based on a …

This paper proposes an approach for robust estimation of highly-varying nonlinear
instantaneous frequency (IF) in monocomponent nonstationary signals. The proposed …