Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse respo...
Compressed sensing(CS) suggests that a signal, sparse in some basis, can be recovered from a small number of random projections. In this paper, we apply the CS theory on sparse ba...
Dikpal Reddy, Aswin C. Sankaranarayanan, Volkan Ce...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Abstract. In this work, we present a direction-of-arrival (DOA) estimation method for narrowband sources impinging from the far-field on a uniform linear array (ULA) of sensors, ba...
The paper introduces a novel iterative method that assigns a reputation to n + m items: n raters and m objects. Each rater evaluates a subset of objects leading to a n × m rating...