Periodic solutions of the Stefan problem with Hysteresis-Type boundary conditions.
In this paper, the problem of obtaining a periodic model in state-space form of a linear process that can be modeled by linear difference equations with periodic coefficients is considered. Such a problem was already studied and solved in [r71] on the basis of the notion of system equivalence, but under the assumption that the process has no null characteristic multiplier. In this paper such an assumption is removed in order to generalize the results in [r71] to linear periodic processes with possibly...
The paper deals with the recently proposed autotracking piecewise cubic approximation (APCA) based on the discrete projective transformation, and neural networks (NN). The suggested new approach facilitates the analysis of data with complex dependence and relatively small errors. We introduce a new representation of polynomials that can provide different local approximation models. We demonstrate how APCA can be applied to especially noisy data thanks to NN and local estimations. On the other hand,...
Poisson driven stochastic differential equations on a separable Banach space are examined. Some sufficient conditions are given for the asymptotic stability of a Markov operator P corresponding to the change of distribution from jump to jump. We also give criteria for the continuous dependence of the invariant measure for P on the intensity of the Poisson process.
In this paper, novel pipelined architectures for the implementation of the frequency domain linear equalizer are presented. The Frequency Domain (FD) LMS algorithm is utilized for the adaptation of equalizer coefficients. The pipelining of the FD LMS linear equalizer is achieved by introducing an amount of time delay into the original adaptive scheme, and following proper delay retiming. Simulation results are presented that illustrate the performance of the effect of the time delay introduced into...