Journal:Informatica
Volume 11, Issue 4 (2000), pp. 411–420
Abstract
This article is an introduction to the simplest mathematical model, which describes the hormone interaction during the menstrual cycle. Modifications of the mathematical model of the menstrual cycle including the mathematical model with the time delay depending on function researched and the mathematical model with the dispersed time delay are researched and described here. A numerical investigation was conducted, during which solutions for the above mentioned models were calculated. The solutions found are compared mutually and with the clinical data.
Journal:Informatica
Volume 11, Issue 4 (2000), pp. 397–410
Abstract
In this paper, the hexagonal approach was proposed for modeling the functioning of cerebral cortex, especially, the processes of learning and recognition of visual information. This approach is based on the real neurophysiological data of the structure and functions of cerebral cortex. Distinctive characteristic of the proposed neural network is the hexagonal arrangement of excitatory connections between neurons that enable the spreading or cloning of information on the surface of neuronal layer. Cloning of information and modification of the weight of connections between neurons are used as the basic principles for learning and recognition processes. Computer simulation of the hexagonal neural network indicated a suitability and prospectiveness of proposed approach in the creation, together with other modern concepts, of artificial neural network which will realize the most complicated processes that take place in the brain of living beings, such as short-term and long-term memory, episodic and declarative memory, recall, recognition, categorisation, thinking, and others.
Described neural network was realized with computer program written on Delfi 3 language named the first order hexagon brainware (HBW-1).
Journal:Informatica
Volume 11, Issue 4 (2000), pp. 381–396
Abstract
An estimation of the generalization performance of classifier is one of most important problems in pattern clasification and neural network training theory. In this paper we estimate the generalization error (mean expected probability of classification) for randomized linear zero empirical error (RLZEE) classifier which was considered by Raudys, Dičiūnas and Basalykas. Instead of “non-explicit” asymptotics of a generalization error of RLZEE classifier for centered multivariate spherically Gaussian classes proposed by Basalykas et al. (1996) we obtain an “explicit” and more simple asymptotics. We also present the numerical simulations illustrating our theoretical results and comparing them with each other and previously obtained results.
Journal:Informatica
Volume 11, Issue 4 (2000), pp. 371–380
Abstract
The accuracy of adaptive integration algorithms for solving stiff ODE is investigated. The analysis is done by comparing the discrete and exact amplification factors of the equations. It is proved that the usage of stiffness number of the Jacobian matrix is sufficient in order to estimate the complexity of solving ODE problems by explicit integration algorithms. The complexity of implicit integration algorithms depends on the distribution of eigenvalues of the Jacobian. Results of numerical experiments are presented.
Journal:Informatica
Volume 11, Issue 4 (2000), pp. 353–370
Abstract
This work is an attempt of generalization of the simple statement about the requirements of commutation of words for the case of languages. In the paper, the necessary condition for commutation of languages are obtained, and in the prefix case the necessary and sufficient conditions are obtained. It is important to note that the considered alphabets and languages can be infinite.
The possibilities of application of the obtained results are shown in the other problems of the theory of formal languages. The boundary problems for the further solution are formulated.
Journal:Informatica
Volume 11, Issue 3 (2000), pp. 325–348
Abstract
In this paper we suggest a three-language (3L) paradigm for building the program generator models. The basis of the paradigm is a relationship model of the specification, scripting and target languages. It is not necessary that all three languages would be the separate ones. We consider some internal relationship (roles) between the capabilities of a given language for specifying, scripting (gluing) and describing the domain functionality. We also assume that a target language is basic. We introduce domain architecture (functionality) with the generic components usually composed using the scripting and target languages. The specification language is for describing user's needs for the domain functionality to be extracted from the system. We present the framework for implementing the 3L paradigm and some results from the experimental systems developed for a validation of the approach.
Journal:Informatica
Volume 11, Issue 3 (2000), pp. 311–324
Abstract
The paper presents new method for sequential classification of the time series observations. Methods and algorithms of sequential recognition are obtained on the basis of the recursive equations for sufficient statistics. These recursive equations allow to construct algorithms of current classification of observable sequences in the rate of entering its values into the on-line operation. Classification algorithms are realized in the form of computer programs, including personal computers. They allow to build multi-channel conveyer computational structures for the sequential recognizers of time series observations.
Journal:Informatica
Volume 11, Issue 3 (2000), pp. 297–310
Abstract
In the previous paper (Pupeikis, 2000) the problem of closed-loop robust identification using the direct approach in the presence of outliers in observations have been considered. The aim of the given paper is a development of the indirect approach used for the estimation of parameters of a closed-loop discrete-time dynamic system in the case of additive correlated noise with outliers contaminated uniformly in it. To calculate current M-estimates of unknown parameters of such a system by means of processing input and noisy output observations, obtained from closed-loop experiments, the recursive robust technique based on an ordinary recursive least square (RLS) algorithm is applied here. The results of numerical simulation of closed-loop system (Fig. 3) by computer (Figs. 4–7) are given.
Journal:Informatica
Volume 11, Issue 3 (2000), pp. 281–296
Abstract
In this paper we present an algorithm for generating quadratic assignment problem (QAP) instances with known provably optimal solution. The flow matrix of such instances is constructed from the matrices corresponding to special graphs whose size may reach the dimension of the problem. In this respect, the algorithm generalizes some existing algorithms based on the iterative selection of triangles only. The set of instances which can be produced by the algorithm is NP-hard. Using multi-start descent heuristic for the QAP, we compare experimentally such test cases against those created by several existing generators and against Nugent-type problems from the QAPLIB as well.
Journal:Informatica
Volume 11, Issue 3 (2000), pp. 269–280
Abstract
The paper presents an intelligent GIS architecture that enables us to extend GIS functionality by using domain specific knowledge and inference engine. In this architecture, an intelligent agent monitors events, which occur in the GIS environment, and execute tasks depending on user's actions. The intelligent agent includes an expert system shell and knowledge base. A hybrid knowledge representation method is used that integrates rule-based, object-oriented, and procedural knowledge representations.