Journal:Informatica
Volume 9, Issue 3 (1998), pp. 297–314
Abstract
More real systems have many components and their simulation requires significant execution times. The practical needs have conducted to distributed simulation rather than sequential method. Asynchronous parallel discrete event simulation (PDES) is studied and its methodology is presented. The paper presents the conservative methodology of PDES and illustrates it with a suggestive particular application: Virtual Assembly Cells.
Journal:Informatica
Volume 9, Issue 3 (1998), pp. 279–296
Abstract
This work is a continuation of our previous papers devoted to exploration of the regular search procedures efficiency in binary search spaces. Here we formulate the problem in a rather general form as a problem of optimization of an unimodal pseudoboolean function given implicitly and obtain analitical estimates of the expected time of a minimum point search for procedures of direct local search. These estimates are polinomial for the case of weakly nonmonotone functions and exponential for the general case of arbitrary unimodal functions. We hope that the proposed result will be usefull first of all for practical applications.
Journal:Informatica
Volume 9, Issue 3 (1998), pp. 259–278
Abstract
This note presents an indirect adaptive control scheme applicable to nominally controllable non-necessarily inversely stable first-order continuous linear time-invariant systems with unmodelled dynamics. The control objective is to achieve a bounded tracking-error between the system output and a reference signal. A least-squares algorithm with normalization is used to estimate the plant parameters by using two additional design tools, namely: 1) a modification of the parameter estimates and 2) a relative adaptation dead-zone. The modification is based on the properties of the inverse of the least-squares covariance matrix and it uses an hysteresis switching function. In this way, the non-singularity of the controllability matrix of the estimated model of the plant is ensured. The relative dead-zone is used to turn off the adaptation process when an absolute augmented error is smaller than the value of an available overbounding function of the unmodelled dynamics contribution plus, eventually, bounded noise.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 235–252
Abstract
In the present paper, the method of structure analysis for multivariate functions was applied to examine the global sensitivity of three complex models: the HIV/AIDS infection spread, radar search, and the multiple criteria decisions.
The investigation of global sensitivity exposed the most influential parameters or their groups. This knowledge makes it possible to concentrate efforts to obtain more exact values of these main parameters.
As a rule, only a small part of model parameters has a significant influence.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 209–234
Abstract
The unique solvability and asymptotic behavior for large time of two cases of symmetric bisexual population model are presented. One of them includes the harmonic mean mating law, while in the other one pair formation occurs only within the same age class.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 195–208
Abstract
This paper considers the control problem of a class of linear hereditary systems subjected to a nonlinear (perhaps) time-varying controller. The absolute stability for a class of nonlinear time-varying controllers are investigated. Sufficient conditions for absolute stability and hyperstability are given.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 173–194
Abstract
This paper addresses the study of the controllability and stability of the equilibrium in economic models which relate the unemployment level to the government expenditure. The interesting cases when the government expenditure is either bounded or a linear function of the national income are specifically considered. The relationships between both variables, namely, unemployment growth level and government expenditure is obtained by considering a Keynesian static model for the national income as well as a differential unemployment-inflation model of Phillips type. Both models are used to derive a new combined one by eliminating the common variable “taxes” which is driven by the investment and government expenditure.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 161–171
Abstract
In this paper we show that the least mean square (LMS) algorithm can be speeded up without changing any of its adaptive characteristics. The parallel LMS adaptive filtering algorithm and its modifications are presented. High speed is achieved by increasing the parallelism in the LMS adaptive algorithm through a proper modification of the LMS adaptive algorithm. An iterative procedures for efficient computation of the lower triangular inverse matrix and the input signal covariance matrix are presented.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 141–160
Abstract
The nonlinearities play a crucial role in the brain processes. They take place in neuronal system elements: synapses, dendrite membranes, soma of neurons, axons. It is established that the soma nonlinearity, which is of sigmoidal shape, is not so strong as compared with the electric current-voltage relation of a dendrite membrane. The relation is N-shaped with two stable and one unstable points. In dynamics, this leads to the appearance of a switch wave or formation of some logic functions. We present some artificial logic circuits based on an electrical analogy of dendritic membrane characteristics in static and dynamic cases. The nonlinear cable theory and the numerical simulation were used. Basing on the logic circuit construction proposed, we suppose that the dendritic membrane processes are able not only to gather and transfer information but also to transform and classify knowledge.
The theoretical substantiation and numerical experiments are only the first step forward to the proving of neuronal dendritic logic constructions. Of course, extensive neurophysiological tests are necessary to discover the final mechanism of neuronal computing in the human brain.