High dimensionality of belief space in Partially Observable Markov Decision Processes (POMDPs) is one of the major causes that severely restricts the applicability of this model. ...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
Finding a good wavelet for a particular application and type of input data is a difficult problem. Traditional methods of wavelet deus on abstract properties of the wavelet that ca...
Research into embedded sensor networks has placed increased focus on the problem of developing reliable and flexible software for microcontroller-class devices. Languages such as ...
Sparse representation in compressive sensing is gaining increasing attention due to its success in various applications. As we demonstrate in this paper, however, image sparse rep...