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.
Journal:Informatica
Volume 9, Issue 2 (1998), pp. 123–140
Abstract
In this paper we describe implementation of numerical adaptive algorithms for multi-dimensional quadrature on distributed-memory parallel systems. The algorithms are targeted at clusters of workstations with standard message passing interfaces, e.g., PVM or MPI. The most important issues are communication and load balancing. Static and dynamic partitioning of the region are considered. Numerical results on various workstation clusters are reported.
Journal:Informatica
Volume 9, Issue 1 (1998): Special Issue on Programming Theory, Information System Engineering, Software Engineering, and Artificial Intelligence, pp. 107–117
Abstract
This paper presents the declarative extension of the deductive database system LOLA to the object-oriented deductive database system O!-LOLA. The model used for O!-LOLA is “objects as theories”, extended by state evolution. O!-LOLA combines logic programming and OO programming in two different ways: First, methods are implemented as logic programs. These methods can be inherited, encapsulated and overloaded. Second, logic programs can be defined over classes, meta-classes, instances, attributes and values. Dynamic updates of attributes of objects and dynamic instantiations of classes are supported.
O!-LOLA is implemented as a preprocessor. O!-LOLA programs are transformed into LOLA rules and facts, which are evaluated set-oriented and bottom-up, using fixpoint semantics. Some object-oriented features concerning dynamic aspects are handled via built-in predicates in LOLA.
We describe the applied theory, the system and the preprocessor, including an example of how methods are translated and we discuss dynamic updates of objects in O!-LOLA.
The benefits of our system in contrast to others are: a single integrated language, clear semantics and a set-oriented evaluation. O!-LOLA uses fixpoint semantics (not any procedural semantics like other systems) and still evaluates set-oriented (and not in a mixed manner like other systems). Thus, we can fully use all optimization techniques developed for deductive databases and gain a very efficient system.