## Journals

- Advances in Mathematics of Communications
- Big Data & Information Analytics
- Communications on Pure & Applied Analysis
- Discrete & Continuous Dynamical Systems - A
- Discrete & Continuous Dynamical Systems - B
- Discrete & Continuous Dynamical Systems - S
- Evolution Equations & Control Theory
- Inverse Problems & Imaging
- Foundations of Data Science
- Journal of Computational Dynamics
- Journal of Dynamics & Games
- Journal of Geometric Mechanics
- Journal of Industrial & Management Optimization
- Journal of Modern Dynamics
- Kinetic & Related Models
- Mathematical Biosciences & Engineering
- Mathematical Control & Related Fields
- Mathematical Foundations of Computing
- Networks & Heterogeneous Media
- Numerical Algebra, Control & Optimization
- AIMS Mathematics
- Conference Publications
- Electronic Research Announcements
- Mathematics in Engineering

### Open Access Journals

DCDS-B

In this paper, we consider a generalized complex network possessing
general topology, in which the coupling may be nonlinear,
time-varying, nonsymmetric and the elements of each node have
different time-varying delays. Some criteria on local and global
exponential synchronization are derived in form of linear matrix
inequalities (LMIs) for the complex network by constructing suitable
Lyapunov functionals. Our results show that the obtained sufficient
conditions are less conservative than ones in previous publications.
Finally, two numerical examples and their simulation results are
given to illustrate the effectiveness of the derived results.

JIMO

In this paper, by using some analytic techniques, several
sufficient conditions are given to ensure the passivity of
continuous-time recurrent neural networks with delays. The passivity
conditions are presented in terms of some negative semi-definite
matrices. They are easily verifiable and easier to check computing
with some conditions in terms of complicated linear matrix
inequality.

keywords:
Passivity
,
linear matrix inequality.
,
neural networks
,
negative semi-definite
matrix
,
delays

DCDS-B

In this paper, self-adaptive proportional control method in economic
chaotic system is discussed. It is not necessarily required for the
fixed point having stable manifold in the method we used. One can
stabilize chaos via time-dependent adjustments of control
parameters; also can suppress chaos by adjusting external control
signals. Two kinds of chaos about the output systems in duopoly are
stabilized in a neighborhood of an unstable fixed point by using the
chaos controlling method. The results show that performances of the
system are improved by controlling chaos. Furthermore, their
applications in practice are presented. The results also show that
players can control chaos by adjusting their planned output or
variable cost per unit according to the sign of marginal profit.

DCDS-B

In this paper, we study the complete synchronization of a class of

*time-varying*delayed coupled chaotic systems using feedback control. In terms of Linear Matrix Inequalities, a sufficient condition is obtained through using a Lyapunov-Krasovskii functional and differential equation inequalities. The conditions can be easily verified and implemented. We present two simulation examples to illustrate the effectiveness of the proposed method.
JIMO

This paper investigates an iterative learning controller for linear discrete-time
systems with state delay based on two-dimensional (2-D) system theory. It shall be
shown that a 2-D linear discrete Roessor's model can be applied to describe the
ILC process of linear discrete time-delay systems. Much less restrictive conditions
for the convergence of the proposed learning rules are derived. A learning algorithm
is presented which provides much more effective learning of control input, which
enables us to obtain a control input to drive the system output to the desired
trajectory quickly. Numerical examples are included to illustrate the performance
of the proposed control procedures.

## Year of publication

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