The massive growth in mobile users and wireless technologies has resulted in increased
data traffic and created demand for additional radio spectrum. This growing demand for …

In the past few decades, with the growing popularity of compressed sensing (CS) in the
signal processing field, the quantization step in CS has received significant attention …

Many contemporary signal processing, machine learning and wireless communication
applications can be formulated as nonconvex nonsmooth optimization problems. Often there …

Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained
considerable attention in array processing thanks to their capability to provide enhanced …

This paper focuses on the problem of student knowledge diagnosis that is a basic task of
realizing personalized education. Most traditional methods rely on the question-concept …

Several Internet-of-Things (IoT) applications provide location-based services, wherein it is
critical to obtain accurate position estimates by aggregating information from individual …

The electrocardiogram (ECG) is widely used for the diagnosis of heart diseases. However,
ECG signals are easily contaminated by different noises. This paper presents efficient …

Functional link artificial neural network (FLANN) has received much attention due to its wide
applicability. The Van der Pol-Duffing oscillator (VdPDO)-based nonlinear systems, which …

This paper presents weighted diffusion least mean p-power (LMP) algorithm for distributed
estimation of an unknown sparse vector in a sensor network. We consider a network, in …

Resource allocation and scheduling in multi-agent systems present challenges due to
complex interactions and decentralization. This survey paper provides a comprehensive …