We consider adaptive identification algorithms based on hyperstability concepts with polyphase structures. The SPR condition required for convergence of these schemes can be always met by using a sufficiently high polyphase expansion factor M: The degree of persistent excitation required for parameter convergence is obtained. If some a priori knowledge about the system to identify is available,...

A method for the stabilization of stationary and timevarying autoregressive models is presented. The method is based on the hyperstability constrained LSproblem with nonlinear constraints. The problems are solved iteratively with Gauss-Newton type algorithm that sequentially linearizes the constraints. The proposed method is applied to simulated data in the stationary case and to real EEG data ...

Asymptotic hyperstability is achievable under certain switching laws if at least one of the feed-forward parameterization: 1) possesses a strictly positive real transfer function, 2) a minimum residence time interval is respected for each activation time interval of such a parameterization, and 3) a maximum allowable residence time interval is guaranteed for all active parameterization which is...

Abstract In this paper we give some hyperstability and stability results for the Cauchy Jensen functional equations on restricted domains. We provide a simple short proof Brzde?k’s result concerning equation.

In this paper, we introduce and solve a new general p-radical functional equation Also, investigate some stability hyperstability results for the considered in 2-Banach spaces. addition, prove of inhomogeneous

This work considers the implementation of recursive identification algorithms based on hyperstability concepts with polyphase structures. It is shown that the SPR condition required for convergence of these schemes can always be met by using a sufficiently high polyphase expansion factor M . For a given M , the degree of persistent excitation required for parameter convergence is obtained. When...

This paper presents a systematic approach for the design of an instrumentation architecture and a sensor data fusion concept which together enable the robust control of complex electromechanical systems. The development is based on the theory of hyperstability. Earlier results are generalized and previous restrictions on sensors are relaxed to broaden the applicability of the proposed method. E...