Gaussian processes (GPs) are versatile tools that have been successfully employed to solve
nonlinear estimation problems in machine learning but are rarely used in signal processing …

In this work we introduce a mixture of GPs to address the data association problem, ie, to
label a group of observations according to the sources that generated them. Unlike several …

Kernel adaptive filtering is a growing field of signal processing that is concerned with
nonlinear adaptive filtering. When implemented naïvely, the time and memory complexities …

Channel measurements are the prerequisite condition for the design of the next-generation
high-speed railway (HSR) communication system. Because of the measurement restriction …

Recent work on multiantenna spectrum sensing in cognitive radio (CR) networks has been
based on generalized likelihood ratio test (GLRT) detectors, which lack the ability to learn …

In recent years, promising results have been reported with the vibrating intrinsic
reverberation chamber (VIRC) combining performance and cost-efficiency for …

This paper presents a novel multiple-input-multiple-output (MIMO) channel sounding
technique with a fully parallel transceiver architecture that employs a layered scheme of …

We introduce a probabilistic approach to the LMS filter. By means of an efficient
approximation, this approach provides an adaptable step-size LMS algorithm together with a …

In order to utilize higher frequency bands above 6GHz, which is an important technical
challenge in fifth generation mobile systems, radio propagation channel properties in a large …

Physical-layer authentication techniques exploit the unique properties of the wireless
medium to enhance traditional higher-level authentication procedures. We propose to …