Develo** a Brain-Computer Interface (BCI) for seizure prediction can help epileptic
patients have a better quality of life. However, there are many difficulties and challenges in …

A new framework for a secure and robust consensus in blockchain-based IoT networks is
proposed using machine learning. Hyperledger fabric, which is a blockchain platform …

A new deep learning-based electroencephalography (EEG) signal analysis framework is
proposed. While deep neural networks, specifically convolutional neural networks (CNNs) …

The focus of this paper is on detection theory for union of subspaces (UoS). To this end,
generalized likelihood ratio tests (GLRTs) are presented for detection of signals conforming …

This paper investigates detection theory for signals belonging to a union of subspaces (UoS)
in the presence of an interference subspace and white noise of unknown variance …

This paper addresses the detection of a signal belonging to several possible subspace
models, namely, a union of subspaces (UoS), where the active subspace that generated the …

This paper deals with learning an overcomplete set of atoms that have low mutual
coherence. To this aim, we propose a new dictionary learning (DL) problem that enables a …

Electroencephalogram (EEG) analysis has garnered attention in the research domain due to
its ability to detect various neural activities starting from brain seizures to a person's …

In this paper, we consider the problem of detecting a target and identifying the subspace that
the target belonging to. The target is assumed to lie in a union of subspaces (UoS) with …

Modern applications in real-world scenarios generate data that are massive and often times
highly structured. Exploiting this structure in an effective manner leads to improved …