Reconfigurable platforms have become a promising solution for high performance signal
processing applications due to their flexible resources, high operating frequency, and low …

Aims: In a face recognition task, it is a challenging problem to find lots of images for a
person. Even, sometimes there can be only one image, available for a person. In these …

High dimensional time series and array-valued data are ubiquitous in signal processing,
machine learning, and science. Due to the additional (temporal) direction, the total …

In this paper, we introduce an Array Memory (AM) processor. The AM processor uses a
shared memory network amenable to on-chip 3D stacking. Node couplings use a 1 to K …

In recent years, the advances in data storage, communication, and computing power have
led to an explosion of data. The demand for data science tasks, such as clustering …

The strong Kronecker product is a very powerful matrix multiplication tool for Hadamard and
other orthogonal matrices from combinatorial theory. Here we show that the strong …

This dissertation presents a new method for the statistical performance analysis of subspace
system identification algorithms. A perturbation expansion of the singular value …

GIAN MATHARU, WENLEI GAO AND MAURICIO D. SACCHI SIAM: MATHEMATICAL &
COMPUTATIONAL ISSUES IN THE GEOSCIENCES, HOUSTON Page 1 Resolution …

Kronecker product is a powerful operation in matrix computations. This paper presents a
technique called multiple Kronecker product sum (or shortly MKPS) approximation. We show …

Least-squares reverse time migration (LS-RTM) for complex fields imaging becomes an
increasingly popular imaging method. It also enjoys some other advantages. For example, it …