We propose a framework for analyzing and comparing distributions, which we use to
construct statistical tests to determine if two samples are drawn from different distributions …

We propose two statistical tests to determine if two samples are from different distributions.
Our test statistic is in both cases the distance between the means of the two samples …

A number of abrupt change detection methods have been proposed in the past, among
which are efficient model-based techniques such as the Generalized Likelihood Ratio (GLR) …

Abstract Intrusion Detection System (IDS) is an effective security tool that helps preventing
unauthorized access to network resources through analyzing the network traffic. However …

The ability to detect online abnormal events in signals is essential in many real-world signal
processing applications. Previous algorithms require an explicit signal statistical model, and …

In the present study, emotion recognition from speech signals was performed by using the
fuzzy C-means algorithm. Spectral features obtained from speech signals were used as …

The ability to detect what unlicensed radios are operating in a neigh borhood, their spectrum
occupancies and the spatial directions their signals are traversing is a fundamental primitive …

Audio segmentation is a basis for multimedia content analysis which is the most important
and widely used application nowadays. An optimized audio classification and segmentation …

Temporomandibular Joint sounds are a very common disorder in the general population.
Temporomandibular Disorder (TMD) is any discomfort related to Temporomandibular Joint …

In this article, we present a new EEG signal classification framework by integrating the
complex-valued and real-valued Convolutional Neural Network (CNN) with discrete Fourier …