—This paper deals with optimized training sequences to estimate multiple-input multiple-output orthogonal frequencydivision multiplexing (MIMO-OFDM) channel states in the presenc...
This paper proposes a compressive sampling scheme based on random temporal sampling using a successive approximation register (SAR) ADC architecture. Variable wordlength data samp...
The recently developed compressive sensing (CS) framework enables the design of sub-Nyquist analog-to-digital converters. Several architectures have been proposed for the acquisit...
John P. Slavinsky, Jason N. Laska, Mark A. Davenpo...
We propose the energy efficient MAC algorithm in this paper. In the proposed algorithm, each node sets the contention window size with respect to the residual energy, the harvest...
—We develop sub-Nyquist sampling systems for analog signals comprised of several, possibly overlapping, finite duration pulses with unknown shapes and time positions. Efficient...
It is now well known that time invariant (TI) linear beamformers, such as the Capon’s beamformer, are only optimal for stationary Gaussian observations whose complex envelope is...
Pascal Chevalier, Abdelkader Oukaci, Jean Pierre D...
In many applications non-stationary Gaussian or stationary nonGaussian noises can be observed. In this paper we present a maximum a posteriori estimation jointly of spectral ampli...
This paper proposes a method for analyzing the direction of the arrival of sound by estimating the sound intensity vector from the pressure and energy gradients of closely-spaced ...
In this work, we propose adaptive frequency-domain biased estimation algorithms with mechanisms to automatically adjust the shrinkage factors. The proposed estimation algorithms i...
In this paper, we propose examining the participants in various meetings or communications within a social network, and using sequential inference based on these participant lists...