Future microprocessors will be highly susceptible to transient errors as the sizes of transistors decrease due to CMOS scaling. Prior techniques advocated full scale structural or...
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
Julien Mairal, Marius Leordeanu, Francis Bach, Mar...
— Sensor networks (SNETs) for monitoring spatial phenomena has emerged as an area of significant practical interest. We focus on the important problem of detection of distribute...
The concept of “Space-Time Sparsity” (STS) penalization is introduced for solving the magnetoencephalography (MEG) inverse problem. The STS approach assumes that events of int...
Andrew K. Bolstad, Barry D. Van Veen, Robert D. No...
Abstract. This paper addresses the detection and reporting of abnormal building access with a wireless sensor network. A common office room, offering space for two working persons...