In this paper, we present a novel architecture based on field-programmable gate arrays
(FPGAs) for the reconstruction of compressively sensed signal using the orthogonal …

Compressive Sampling reconstruction techniques require computationally intensive
algorithms, often using L 1 optimization to reconstruct a signal that was originally sampled at …

Even though chitin is one of the most abundant biopolymers in nature, current knowledge on
chitin formation is largely based only on data from fungi and insects. This study reveals …

The nature of modern astronomy means that a number of interesting problems exhibit a
substantial computational bound and this situation is gradually worsening. Scientists …

In this paper we present a novel hardware architecture for reconstruction of signals in
compressed sensing. The proposed architecture is based on the orthogonal matching …

Sparse signal recovery becomes extremely challenging for a variety of real-time
applications. In this paper, we improve the orthogonal matching pursuit (OMP) algorithm …

Compressed sensing (CS) is a revolutionary signal acquisition theory, enabling signal
acquisition at a rate that is below the Nyquist sampling rate. However, CS signal …

This paper proposes a high performance least square solver on FPGAs using the Cholesky
decomposition method. Our design can be realized by iteratively adopting a single triangular …

Massive multi-user (MU) MIMO wireless technology promises improved spectral efficiency
compared to that of traditional cellular systems. While data-detection algorithms that rely on …

Solving large optimization problems within the energy and cost budget of mobile SoCs in
real-time is a challenging task and motivates the development of specialized hardware …