In this paper we consider the output consensus problem of networked Hammerstein and Wiener systems in a noisy environment. The Hammerstein or Wiener system is assumed to be open-loop stable, and its static nonlinearity is allowed to grow up but not f...

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With the aid of Maple symbolic computation and Lie group method, (2+1)-dimensional PBLMP equation is reduced to some (1+1)-dimensional PDE with constant coefficients. Using the homoclinic test technique and auxiliary equation methods, we obtain new e...

We give some inequalities of capacity in Gaussian channel with or without feedback. The nonfeedback capacity $C_{n,Z}(P)$ and the feedback capacity $C_{n,FB,Z}(P)$ are both concave functions of $P$. Though it is shown that $C_{n,Z}(P)$ is a convex fu...

This paper deals with the parameter estimation problem of the Single-Input-Single-Output (SISO) switched Hammerstein system. Suppose that the switching law is arbitrary but can be observed online. All subsystems are parameterized and the Recursive Le...

In this paper we present a general convex optimization approach for solving high-dimensional multiple response tensor regression problems under low-dimensional structural assumptions. We consider using convex and weakly decomposable regularizers assu...

In this paper, we consider the problem of learning high-dimensional tensor regression problems with low-rank structure. One of the core challenges associated with learning high-dimensional models is computation since the underlying optimization probl...

The effects of the applied field, cell size, and cutting area on the ‘‘seed’’ induced magnetic reversal of a cobalt element array have been studied by a stochastic dynamic micromagnetics code using the Laudau–Lifshitz–Gilbert equation. Three magnetic...

Monte Carlo simulations using a three-dimensional lattice model studied the Ruderman–Kittel–Kasuya–Yosida (RKKY) indirect exchange interaction of doped magnetic Co ions in ZnOfilms. The results of the calculations show that the RKKY interaction in Co...

In the paper, a novel distributed stochastic approximation algorithm (DSAA) is proposed to seek roots of the sum of local functions, each of which is associated with an agent from the multiple agents connected in a network. At any time, each agent up...