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    • On the Inspection of Classification Results in the Fuzzy Clustering Method Based on the Allotment Concept 

      Viattchenin, Dmitri A. (BrSTU, 2006)
      Viattchenin, Dmitri A. On the Inspection of Classification Results in the Fuzzy Clustering. Method Based on the Allotment Concept / Dmitri A. Viattchenin // International Conference on Neural Networks and Artificial Intelligence : proceedings, Brest, 31 May – 2 June, 2006 / Edited: V. Golovko [et al.]. ...

      2023-11-23

    • A Modification of the FCM-CV-algorithm and Its Application for Radar Portraits Classification 

      Sadowska, Krystyna; Sharamet, Andrei (BrSTU, 2006)
      Sadowska, K. A Modification of the FCM-CV-algorithm and Its Application for Radar Portraits Classification / K. Sadowska A. Sharamet // International Conference on Neural Networks and Artificial Intelligence : proceedings, Brest, 31 May – 2 June, 2006 / Edited: V. Golovko [et al.]. – Brest : BSTU, ...

      2023-11-23

    • Classification of handwritten signatures based on boundary tracing 

      Adamski, Marcin; Saeed, KhaIid (BrSTU, 2006)
      The paper presents a system for offline classification of handwritten signatures. The algorithm is based on boundary tracing technique for extracting characteristic features. Outer and inner boundaries are treated separately. The upper and lower parts of the boundaries are extracted to form two sequences ...

      2023-11-23

    • Five Strategies of the Self-Tutoring of a Neural Networks by E. Sokolov 

      Losik, George (BrSTU, 2006)
      The bionic models of neural networks are of interest. A bionic model that suggested by Prof. E. Sokolov consisting of detectors and control neurons. In his model the self-tutoring is designed, the environment and a purpose of neural network's behaviour are considered. In this article five various ...

      2023-11-23

    • Can neural networks holistically reprogram themselves through their own observation? 

      Mariage, Jean-Jacques (BrSTU, 2006)
      Neural networks (NNs) are inspired -at least metaphorically -from biological solutions nature selected by evolution. On one hand, learning algorithms' efficacy has been widely demonstrated experimentally, even if the mathematical proof of their convergence is not always very easy to establish (SOM). ...

      2023-11-23

    • Learning From The Environment With A Universal Reinforcement Function 

      Bendersky, Diego; Santos, Juan Miguel (2006)
      Traditionally, in Reinforcement Learning, the specification of the task Ls contained in the reinforcement function (RF), and ach new task requires the definition of a new RF. But in the nature, explicit reward signals are limited, and the characteristics of the environment afTects not only how animals ...

      2023-11-23

    • Comparative Analysis of Neural Networks and Statistical Approaches to Remote Sensing Image Classification 

      Kussul, Nataliya; Skakun, Serhiy; Kussul, OIga (BrSTU, 2006)
      This paper examines different approaches to remote sensing images classification. Included in the study are statistical approach, namely Gaussian maximum likelihood classifier, and two different neural networks paradigms: multilayer pcreeptron trained with EDBD algorithm, and ARTMAP neural network. ...

      2023-11-24

    • Image Representation Based Hybrid Intelligent Diagnosis Approach for Computer Aided Diagnosis (CAD) Systems 

      Chohra, Amine; Kanaoui, Nadia; Madani, Kurosh (BrSTU, 2006)
      Computer Aided Diagnosis (CAD) is one of the most interesting and most difficult dilemma dealing in one hand with expert (human) knowledge consideration. On the other hand, fault diagnosis is a complex and fuzzy cognitive process and soft computing approaches as modular neural networks and fuzzy logic, ...

      2023-11-24

    • A Framework for Parallel Processing of Image Dataflow in Industrial Applications 

      Otwagin, Aleksej; Doudkin, Alexander (BrSTU, 2006)
      Basic algorithms and processing technologies of integrated circuit layout images are considered. The images represented as a set of frames can regard as a dataflow and the processing are perfectly suited for parallel implementation. Framework architecture for designing parallel systems of image dataflow ...

      2023-11-24

    • An Approach to Solving Face Detection Task 

      Krasnoproshin, Viktor Vladimirovich; Koblov, E. V. (BrSTU, 2006)
      In this paper a pattern-recognition based approach to solving face detection task is proposed. All main steps are revealed and algorithms for their solution are built. It is shown that these algorithms in the aggregate effectively solve the face detection task. The conditions when the exact solution ...

      2023-11-24

    • A Neural Network Based Speech Recognition System For Isolated Tamil Words 

      Bharath, B.; DeepaIakshmi, V.; Nelson, I. (BrSTU, 2006)
      Speech recognition is always looked upon as a fascinating field in human computer interaction. It is one of the fundamental steps towards understanding human cognition and their behavior. White most of the literature on speech recognition is based on Hidden Markov Models (HMM). This paper presents a ...

      2023-11-24

    • Resampling-down Mesh based Discriminant Filter Synthesis for Face Recognition 

      Samokhval, V. A. (BrSTU, 2006)
      Presented paper addresses face recognition algorithm by means o f synthetic discriminant filters synthesized in pseudo 3-D mesh domain. The objective of the research is to construct facial descriptor in the form of linear filter, which should produce high and low outputs for intra- and inter-class ...

      2023-11-24

    • View-Based Word Recognition System 

      Tabedzki, Marek; Khalid, Saeed (BrSTU, 2006)
      In this paper, a new method for word recognition and classification without segmentation is presented. The worked out algorithm is based on recognizing the whole word without separating it into letters. According to this algorithm, entire words are treated and analyzed as object images subject to ...

      2023-11-24

    • An Approach to Interplanetary Shocks Prediction Using Single ACE/EPAM Channel Data 

      Turchcnko, Volodymyr; Demchuk, Viktor; Sachenko, Anatoly; Veremeyenko, Yuri (BrSTU, 2006)
      An approach to prediction of the arrival time of interplanetary shocks using neural networks based on the data gathered from single EPAM (Electron, Proton and Alpha Monitor) channel o f NASA's ACE (Advanced Composition Explorer) spacecraft is proposed in this paper. A short description of ACE spacecraft ...

      2023-11-24

    • Neural Networks for Chaotic Signal Processing: Application to the Electroencephalogram Analysis for Epilepsy Detection 

      Головко, Владимир Адамович; Безобразова, Светлана Владимировна (BrSTU, 2006)
      Many techniques were used in order to detect and to predict epileptic seizures on the basis of electroencephalograms. One of the approaches for the prediction of epileptic seizures is the use the chaos theory, namely determination largest Lyapunov's exponent or correlation dimension of scalp EEG ...

      2023-11-27

    • A weighting function approach for neural network nonlinear time series analysis of satellite remote sensing of rainstorms 

      Lisheng Xu; Jilie Ding; Xiaobo Deng (BrSTU, 2006)
      One of frequently used neural networks, i.e., a radial-based function network (RBFN) with Gaussian activation functions is employed to study the nonlinear time series by carrying out the characterization experiments for a GMS- 5 satellite 11 µm IR observations of rainstorm process. The proposed ...

      2023-11-27

    • Fatigue Crack Growth Prediction via Artificial Neural Network Technique 

      Nechval, Konstantin N.; Bausova, Irina; ŠķiItere, Daina; Nechval, Nicholas A.; Strelchonok, Vladimir F. (BrSTU, 2006)
      The artificial neural network (ANN) technique for the data processing of on-line fatigue crack growth monitoring is proposed after analyzing the general technique for fatigue crack growth data. A model for predicting the fatigue crack growth by ANN is presented, which does not need all kinds of materials ...

      2023-11-27

    • Matching on Graphs 

      Shut, Vasily Nikolaevich; Svirsky, V. M.; Solomiyuk, K. S.; Gryazev, E. V. (BrSTU, 2006)
      This work is devoted to development of new algorithm of the decision of a matter about matching. In the result the algorithm of search maximal matching in graphs has been developed and realized, the estimation of its complexity, and comparison with existing algorithms have been made. Its characteristics, ...

      2023-11-27

    • On Application of the Ternary Matrix Cover Technique for Minimization of Boolean Functions 

      Pottosin, Yu. V.; Shestakov, E. A. (BrSTU, 2006)
      To solve the task of recognizing features of objects used in expert systems the Boolean function approach can be attracted. In particular, the relation between the features can be given as a disjunctive normal form (DNF) of the Boolean function whose arguments correspond to the features, and the rise ...

      2023-11-27

    • Soft Computing as a solution to Time/ Cost Distributor 

      Nabil M. Hewahi (BrSTU, 2006)
      In this paper we present a theoretical model based on soft computing to distribute the time/cost among the industry/machine sensors or effectors based on the type of the application. One of the most unstudied significant work is to recognize which sensor in an industry for example has higher priority ...

      2023-11-27