One of the most important properties of neural networks is the clustering of local minima of
the loss function near the global minimum, enabling efficient training. Though generative …

Clustering time series into similar groups can improve models by combining information
across like time series. While there is a well developed body of literature for clustering of …

In some radar applications, neither the channel parameters nor the transmitted signal are
known a-priori at the radar receiver. As such, both the transmitted signal as well as the …

Massive multiple-input multiple-output (MIMO) in time-division duplexing (TDD) systems
relies on the channel reciprocity to obtain the downlink (DL) channel state information (CSI) …

Full-duplex (FD) relaying is more spectrally efficient compared to its counterpart,
conventional half-duplex (HD) relaying, since it allows simultaneous transmission and …

In a multicell environment, the half-duplex (HD) relaying is prone to inter-relay interference
(IRI) and the full-duplex (FD) relaying is prone to relay residual-interference (RSI) and relay …

This paper deals with the Elliptical Wishart and Inverse Elliptical Wishart distributions, which
play a major role when handling covariance matrices. Similarly to multivariate elliptical …

In this work, we consider the weighted difference of two independent complex Wishart
matrices and derive the joint probability density function of the corresponding eigenvalues in …

Multiple input multiple output (MIMO) approach in fiber optical communication has emerged
as an effective proposition to address the ever increasing demand for information exchange …

Random matrices are nowadays classical tools for modeling multiantenna wireless
channels. Scattering phenomena typical of cellular frequencies and channel reciprocity …