Informatica

Control laws' design strategies in order to stabilize integro-differential systems with delays are developed by using an extended system and the delay measure.

In this paper we present the development of the nationwide information infrastructure in Lithuania. The paper describes the general framework of Lithuania's information infrastructure, basic philosophy behind it, and the current solution of the problem from the point of view registers, data network, standards and application systems.

The convergence properties of some LOD schemes are considered. New stability estimates with respect to boundary conditions are proved. These results are used to investigate the accuracy of LOD schemes when no special boundary correction technique is used for the realization of LOD schemes. The accuracy of LOD schemes with corrected boundary conditions is also investigated. Results of the computational experiment are given.

The problem of the parameters estimation of quasihomogeneous autoregressive random field is considered. An algorithm is proposed for the parameter estimation of certain classes of such fields.

In this paper we consider the numerical solution of the large system of nonlinear differential equations. We assume that the system simulates the semiconductor circuit. We apply the well known event driven techniques to get some approximation of solution fast. We extend those techniques by considering pairs of nodes, instead of single nodes, as usual. The “pairwise” solution is more efficient in tightly coupled circuits. The improvement of efficiency of solution is important optimizing the parameters of circuits. In many cases we need the global optimization of equation parameters. Then, the modeling speed could be the main factor of successful application.

The structure of a multimicroprocessor systems (MS) of M microprocessors (MP) and N blocks of random access memory (RAM) is presented. Probability techniques were applied to compile mathematical models which reflect random processes both in the whole structure and in its surroundings, as well as the links in the system units, specific operation features of the MP and the different data flows.

We consider finite population slotted ALOHA where each of n terminals has its own transmission probability pi. Given the overall traffic load λ, the probabilities pi are determined in such a way as to maximize throughput. This is achieved by solving a constrained optimization problem. The results of Abramson (1970) are obtained as a special case. Our recent results are improved (Mathar and Žilinskas, 1993).

The problem associated with the stiff ordinary differential equation (ODE) systems in parallel processing is that the calculus can not be started simultaneously on many processors with an explicit formula. The proposed algorithm is constructed for a special classes of stiff ODE, those of the form y′(t)=A(t)y(t)+g(t). It has a high efficiency in the implementation on a distributed memory multiprocessor when the ODEs function has many components. The approximation error is equal to that produced by the analogous sequential algorithm.

This paper establishes sufficient conditions for stability of linear and time-invariant delay differential systems including their various usual subclasses (i.e., point, distributed and mixed point-distributed delay systems). Sufficient conditions for stability are obtained in terms of the Schur's complement of operators and the frequency domain Lyapunov equation. The basic idea in the analysis consists in the use of modified Laplace operators which split the characteristic equation into two separate multiplicative factors whose roots characterize the system stability. The method allows a simple derivation of stabilizing control laws.

The restoration of an entire epicortical ECoG-potential pattern from spatially sampled EEG-potentials can be performed according to the general principle of inverse spatial filtering: if a forward spatial filter is an averaging one, then a mutually inverse spatial filter can form a sharpened pattern from a slurred sampled pattern thus restoring more or less a spatial contrast of a primary source pattern. Brain coverings are the averaging forward spatial time-lag free filter in the transformation “eECoG $\longrightarrow$ EEG”; several models have been already developed for calculating the weight coefficients of this filter. Proposed here method to obtain weight coefficients of the mutually inverse spatial time-lag free filter of EEG is based on the generalized inversion of forward filter's weight coefficients matrix. The developed algorithm is verified using 3-dimensional depiction of numerically simulated patterns: the “real” eECoGs are visually compared with the restored eECoGs, that were obtained from the corresponding spatial samples of the “real” EEGs.