Over the last decade, kernel methods for nonlinear processing have successfully been used
in the machine learning community. The primary mathematical tool employed in these …

This paper presents a wide framework for non-linear online supervised learning tasks in the
context of complex valued signal processing. The (complex) input data are mapped into a …

The present report, has been inspired by the need of the author and its colleagues to
understand the underlying theory of Wirtinger's Calculus and to further extend it to include …

This paper extends the worst-case performance optimization based robust Capon
beamformer (RCB) to the generalized case with possible noncircular signal-of-interest (SOI) …

Although the real reproducing kernels are used in an increasing number of machine
learning problems, complex kernels have not, yet, been used, in spite of their potential …

The fundamental task of classification given a limited number of training data samples is
considered for physicalsystems with known parametric statistical models. The standalone …

This paper deals with receiver design for the uplink of a single-carrier interleaved frequency-
division multiple-access (SC-IFDMA) system, which is a promising candidate for non …

The fundamental task of classification given a limited number of training data samples is
considered for physical systems with known parametric statistical models. As a solution, a …

This paper considers a multiple-input multiple-output (MIMO) orthogonal frequency-division
multiplexing (OFDM) wireless network contaminated by Middleton Class A impulsive noise …

In wireless systems noise mitigation is a significant factor for competent working. Impulsive
noise is one of the most important sources of performance degradation in wireless systems …