In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
We investigate classification of non-linguistic vocalisations with a novel audiovisual approach and Long Short-Term Memory (LSTM) Recurrent Neural Networks as highly successful d...
Radio Frequency (RF) tomographic tracking is the process of tracking moving targets by analyzing changes of attenuation in wireless transmissions. This paper presents a novel sequ...
This work focuses on the convergence analysis of adaptive distributed beamforming schemes that can be reformulated as local random search algorithms via a random search framework....
Multiclass classification problems are often decomposed into multiple binary problems that are solved by individual binary classifiers whose results are integrated into a final...
We show that equiangular tight frames (ETFs) are particularly well suited as additive fingerprint designs against Gaussian averaging collusion attacks when the number of users is...
Dustin G. Mixon, Christopher J. Quinn, Negar Kiyav...
Block transmission of multi-scale orthogonal wavelet division multiplexing (OWDM) is proposed for signaling over wideband linear time-varying channels (LTV). Such channels are bes...
In this paper we describe a new approach for the estimation of the porosity and its uncertainty from Nuclear Magnetic Resonance relaxation measurements in porous media. The new ap...
Fred K. Gruber, Lalitha Venkataramanan, Denise E. ...
This paper provides an analysis of the impacts of machine translation and speech synthesis on speech-to-speech translation systems. The speech-to-speech translation system consist...
Kei Hashimoto, Junichi Yamagishi, William J. Byrne...
Interior tomography is an emerging area, which is for theoretically exact reconstruction of an internal region of interest (ROI) only from local projection data directly associate...