Journal:Informatica
Volume 6, Issue 2 (1995), pp. 233–243
Abstract
The newest version of Turbo Pascal – Turbo Pascal 7.0 – is concentrately described in comparing with optimal language for programming teaching – Standard Pascal. Data types, control structures, procedures and functions, parameters, new directions of development are classified and discussed.
Journal:Informatica
Volume 6, Issue 2 (1995), pp. 225–232
Abstract
An algorithm for the sequential analysis of multivariate data structure is presented. The algorithm is based on the sequential nonlinear mapping of L-dimensional vectors from the L-hyperspace into a lower-dimensional (two-dimensional) vectors such that the inner structure of distances among the vectors is preserved. Expressions for the sequential nonlinear mapping are obtained. The mapping error function is chosen. Theoretical minimum amount of the very beginning simultaneously mapped vectors is obtained.
Journal:Informatica
Volume 6, Issue 2 (1995), pp. 193–224
Abstract
We apply some concepts of Information-Based Complexity (IBC) to global and discrete optimization. We assume that only partial information on the objective is available. We gather this partial information by observations. We use the traditional IBC definitions and notions while defining formal aspects of the problem. We use the Bayesian framework to consider less formal aspects, such as expert knowledge and heuristics.
We extend the traditional Bayesian Approach (BA) including heuristics. We call that a Bayesian Heuristic Approach (BHA).
We discuss how to overcome the computational difficulties using parallel computing. We illustrate the theoretical concepts by three examples: by discrete problems of flow-shop scheduling and parameter grouping, and by a continuous problem of batch operations scheduling.
Journal:Informatica
Volume 6, Issue 2 (1995), pp. 181–192
Abstract
Rule-based systems are usually interpreted as a shallow expert systems realization tool. The paper analyses how the applicability of production rules can be extended using the proposed rule base structuring discipline. Its main constructions are rule grouping according to elementary aspects of investigation, and decomposition of actions. In addition, the rule cycle construction is used for discrete time simulation tasks. The proposed method is illustrated by 2 applications: the expert subsystem for a database, and the simulator of a water heater.
Journal:Informatica
Volume 6, Issue 2 (1995), pp. 167–180
Abstract
The use of vector quantization for speaker identification is investigated. This method differs from the known methods in that the number of centroids is not doubled but increases by 1 at every step. This enables us to obtain identification results at any number of centroids. This method is compared experimentally with the method (Lipeika and Lipeikienė, 1993a, 1993b), where feature vectors of investigative and comparative speakers are compared directly.
Journal:Informatica
Volume 6, Issue 2 (1995), pp. 123–166
Abstract
This paper investigates the progress made in the field of dynamic systems with delays over the last two decades. In particular, it is focused on the simulation and control techniques, which include also modelling, numerical solvability and stabilization procedures.
Journal:Informatica
Volume 6, Issue 1 (1995), pp. 93–117
Abstract
This work is our first attempt in establishing the connections between evolutionary computation algorithms and stochastic approximation procedures. By treating evolutionary algorithms as recursive stochastic procedures, we study both constant gain and decreasing step size algorithms. We formulate the problem in a rather general form, and supply the sufficient conditions for convergence (both with probability one, and in the weak sense). Among other things, our approach reveals the natural connection of the discrete iterations and the continuous dynamics (ordinary differential equations, and/or stochastic differential equations). We hope that this attempt will open up a new horizon for further research and lead to in depth understanding of the underlying algorithms.
Journal:Informatica
Volume 6, Issue 1 (1995), pp. 85–92
Abstract
The problem of construction of the fuzzy classification models (fuzzy classifiers) with high generalization ability is discussed. The strong self guessing property of fuzzy classificational models is introduced and examined. It is proved that this characteristic doesn't form a full system of restrictions, i.e., for the unambiguous detection of the most valid fuzzy classifier (among the set of fuzzy classifiers agreed with arbitrary learning set) it is necessary to use additional “regularizing” restrictions.
Journal:Informatica
Volume 6, Issue 1 (1995), pp. 71–84
Abstract
The aim of the given paper is the development of optimal and tuned models and ordinary well-known on-line procedures of unknown parameter estimation for inverse systems (IS) using current observations to be processed. Such models of IS are worked out in the case of correlated additive noise acting on the output of the initial direct system (DS). The results of numerical investigation by means of computer (Table 1) are given.
Journal:Informatica
Volume 6, Issue 1 (1995), pp. 61–70
Abstract
One objective of this paper is to estimate the parameters p,d,q of an autoregressive fractionally integrated moving average ARFIMA (p,d,q) stochastic model by minimizing the squares of the residuals using a Bayesian global optimization techniques. We consider bilinear model, too because it is the simple extension of linear model, defined by adding a bilinear term to traditional ARMA model. Therefore, the second objective of the paper is to estimate parameters of a bilinear time series.