The approach of least squares (LSs) has been quite popular and widely adopted for the
common linear regression analysis, which can give rise to the solution to an arbitrary …

In this article, we present a novel approach to reconstruct the topology of networked linear
dynamical systems with latent nodes. The network is allowed to have directed loops and bi …

Quantization is an important technique to transform the input sample values from a large set
(or a continuous range) into the output sample values in a small set (or a finite set). It has …

As a key technology of network inference, topology sensing plays an important role in
understanding, explaining and predicting network behavior. Majority of existing studies …

In recent years, tensors have been applied to different applications in science and
engineering fields. In order to establish theory about tail bounds of the tensors summation …

This article addresses the problem of reconstructing the topology of a network of agents
interacting via linear dynamics, while being excited by exogenous stochastic sources that …

Accurate network topology information serves as the foundation for the operation of active
control and active management, which have become indispensable requirements for the …

Topology sensing of non-collaborative wireless networks is a challengingtask due to the
limited available information resulting from the inherent non-collaborative characteristics. To …

This work prepares new probability bounds for sums of random, independent, Hermitian
tensors. These probability bounds characterize large-deviation behavior of the extreme …

Neural decoding is still a challenging and a hot topic in neurocomputing science. Recently,
many studies have shown that brain network patterns containing rich spatiotemporal …