Currently, some works on studying complete synchronization of dynamical systems are usually restricted to its two special cases: 1) power-rate and 2) exponential synchronization. Therefore, how give a generalization these types by the mathematical expression is an open question that needs be urgently solved. To begin with, this article proposes multimode function for first time, which synchroni...

This article presents a new parameter estimation algorithm for the adaptive control of class time-varying plants. The main feature this is matrix learning rates, which enables error trajectories to tend exponentially fast toward compact set whenever excitation conditions are satisfied. employed in large problems where unknown parameters present and time-varying. It shown that guarantees global ...

In this paper, we present a new method for modeling timeevolving correlation networks, using a Mean Reversion Autoregressive Model, and apply this to stock market data. The work is motivated by the assumption that the price and return of a stock eventually regresses back towards their mean or average. This allows us to model the stock correlation time-series as an autoregressive process with a ...

In this paper, it is shown that the least squares algorithm with covariance reset, which is originally developed for the purpose of constant parameter identification, can be effectively applied to the observer design for a general linear time-varying system. The new observer successfully avoids many of the disadvantages of other time-varying observers, such as slow convergence rate, heavy compu...

A systematic approach to joint state and time-varying parameter estimation for nonlinear systems is proposed in this paper. Applying the sector nonlinearity transformation to both the system nonlinearities and the time-varying parameters, the original system is equivalently rewritten as a Takagi-Sugeno system with unmeasurable premise variables. A joint state and parameter observer whose parame...