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    • Dynamiс Planning in Spacecraft Approaching and Docking Control 

      Winogradov, A. N.; (BPI, 1999)
      In this paper problems o f spacecraft control automatization on the stages of approaching and docking are considered. For sohing these problems, we are offer using onboard scheduler, based on rules. Onboard scheduler, based on dynamie planning methods, developing in artificial intelligence researches, ...

      2021-07-27

    • Unsupervised Training Algorithm for Recirculation Neural Network 

      Golovko, V.; Gladyschuk, V. (BPI, 1999)
      Unsupemised learning is the great promise of the future. In such training the network is provided with inputs but not with desired outputs. Unsupemised learning is used for the principal component networks. This paper describes a nerw method for training of the recirculation networks. Such method is ...

      2021-07-27

    • Reactive Control of a Mobile Robot Based on Neural Networks 

      Golovko, V. (BPI, 1999)
      This paper describes the neural system for reactive control of the mobile robot. The neural system consists of different types of neural networks, which are combined in the intelligent system. The efficient techniques for the training of neural networks are considered. The main problem of the neural ...

      2021-07-27

    • Synthesis of a Test Generator for a Built-ln Self-Test Scheme 

      Khomich , O. V.; Yarmolik, V. N. (BPI, 1999)
      This paper presents a new algorithm for the automated synthesis of pseudo-random test patterns generators for Built-ln Self Test schemes with a mixed testmode. The experimental resulls showan opportunity of using the given method on a design stage of circuits producing In this paper it is shown that ...

      2021-07-27

    • Multi-Scale Image Analysis and Applications in Framework of the Intas 96-785 Project 

      Heijmans, H. J. A. M.; Kirichuk, V. S.; Kovalev, V. A.; Pauwels, E. J.; Petrou, M.; Tsurkov, V. I.; Tuzikov, А. V. (BPI, 1999)
      Multi-Scale Image Analysis and Applications in Framework of the Intas 96-785 Project / H. J. A. M. Heijmans [and etc.] // International Conference on Neural Networks and Artificial Intelligence ICNNAI’99 = Международная конференция по нейронным сетям и искусственному интеллекту ICNNAI’99 : Proceedings, ...

      2021-07-27

    • The Application of Self-Organizing Neural Networks in Financial Market Analysis 

      Stankevicius, G. (BPI, 1999)
      The problem of comparison of different companies is facing, when analyzing company's performance in stock exchange market. Due to many different fmancial ratios and parameters sometimes it is almost impossible to decide which company is a leader or not. One of the ways to solve this problem is the use ...

      2021-07-27

    • Neuroelectronic Systems: Binding Neurons to Electric Circuits 

      Molchanov, P. G.; Denisov, A. A.; Martinovich, G. G.; Cherenkevich, S. N. (BPI, 1999)
      This paper is devoted to description of a new type of information system based on interaction of biological neurons and electronic components – neuroelectronic (NE) system. Main features and components, like neural network sensor, of NE are briefly put into consideration followed with an example of ...

      2021-07-27

    • New Approach of the Recurrent Neural Network Training 

      Golovko, V.; Savitsky, Y. (BPI, 1999)
      In this work the technique o f creation o f adapthre training algorithms for recurrent neural networks (RNN) is cortsidered. These algorithms have high convergence and accuracy on a comparison with traditional backpropagation. The original technique of calculation of an adaptive training step with use ...

      2021-07-27

    • Intelligent System for Prediction of Sensor Drift 

      Golovko, V.; Savitsky, Y.; Sachenko, A.; Kochan, V.; Turchenko, V.; Laopoulos, T.; Grandinetti, L. (BPI, 1999)
      ln this paper the features of neural networks using for improve of measurement accuracy of physical quantities by sensor drift prediction are considered. There is use a technique of data volume increasing for training of predicting neural network by using of separate approximating neural network.

      2021-07-27

    • The Training of Feed-Forward Neural Networks 

      Golovko, V.; Dunets, A.; Savitsky, Y. (BPI, 1999)
      The training of multilayer perceptron is generally a difficult task. Excessive training times and lack of convergence to an acceptable solution are frequently reported. This paper discribes new training methods of feedforward neural networks. In comparison with standard backpropagation algorithm it ...

      2021-07-27

    • Architecture of Computer Vision Software System 

      Ivkin, A.; Doudkin, A.; Sadykhov, R. (BPI, 1999)
      The software o f the Computer vision systems is complicated. The authors discuss the principles of Computer vision systems organization and propose the architecture for such software system.

      2021-07-27

    • Temporal Processing Neural Networks for Speech Recognition 

      Ivanov, A. V.; Petrowsky, A. A. (BPI, 1999)
      Application of the temporal processing neural networks (TPNNs) to the speech recognition is justifled by the nature of the task. Indeed ASR is a sequence recognition problem and assumes incorporation of time into decision process. Static models treat elements of sequence as independent patterns, which ...

      2021-07-27

    • The Approach of the Shortest Path Planning Problem Solution on the Basis of a Neural Network 

      Dimakov, V. (BPI, 1999)
      This paper describes the neural network solving the shortest path planning problem. It consists of the layer set, where each layer forms a path-candidate for the fixed number of cities. During competition the layer-winner determining the sequence order of cities in the shortest path is selected. In ...

      2021-07-27

    • Self-training Neural System for Autonomous Control of a Mobile Robot 

      Golovko, V.; Ignatiuk, O. (BPI, 1999)
      Unsupervised training is of great importance for adaptation to the emironment. This adaptation is performed by means of continuos training as a result of interaction between robot and emironment. In this case the teacher is the emironment. This paper presents the way for the implementation of unsupervised ...

      2021-07-27

    • Є-insensitive Unsupervised Learning 

      Fyfe, C.; Gabrys, B. (BPI, 1999)
      One of the major paradigms for unsupervised learning in Artificial Neural Networks is Hebbian learning. The standard implementations of Hebbian learning are optimal under the assumptions of Gaussian noise in a data set. We derive e-insensitive Hebbian learning based on minimising the least absolute ...

      2021-07-27

    • Social Dynamics and Self-Organizing 

      Golovko, V.; Borisyuk, Z. (BPI, 1999)
      A view of dynamics and self-organizing of social systems is presented. Both a separate Homo sapiens and human society are viewed as social systems. The dynamics of the development of such systems is also examined.

      2021-07-27

    • On the Detecting of Symmetries of Switching Functions for Eflicient Design of Decision Trees and Decision Diagrams 

      Popel, D.; Popel, E. (BPI, 1999)
      This paper presents an approach to detect symmetries of switching functions for efficient design of Reed-Muller decision trees (DTs) and decision diagrams (DDs). The information theory measures of switching functions are used to determine possible symmetric variabies and therefore to reduce search ...

      2021-07-27

    • Artificial Neural NetWork for DTMF decoders 

      Aiello, A.; Daponte, P.; Grimaldi, D.; Michael, L. (BPI, 1999)
      In this paper, the paltem recognition characteristics of the Artificial Neural Networks (ANNs) are used to realise a real decoder for Dual Tоnе Multi Frequency signals used in the telecommunication field. A new neural architecture, the Multi Leaming Vector Quantization (MLVQ) network, is proposed It ...

      2021-07-27

    • Application of Genetic Algorithms for Solutions of the Task Is Frequent – Territorial Plannings Group Radio Electronic Equipment 

      Kulaga, V. V.; Muravjev, S. A.; Spiridonov, S. V.; Telyatnikov, R. V. (BPI, 1999)
      One from the important problems, is a problem of limited frequencyТs number between radio electronic equipment's (REE) within large group. It is necessary that all REE may operate with specific correlation of signal-noise (interference) on boundaries of their service's zones, сon sideling of electromagnetic ...

      2021-07-27

    • Decomposition Approach to Minimize a Class of Superposition of Recurrent Monotone Functions on a Set of Parameterized Paths in Digraph 

      Guschinsky, N.; Levin, G. (BPI, 1999)
      A problem of finding optimal parameterized path in digraph is considered. A parameterized path is a path each arc of which is assigned a parameter fforn a given set. A superposition of recurrent-monotone functions is accepted as an objective fimction where one of the functions is defined by using max ...

      2021-07-27