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Now showing items 1-20 of 37

    • 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

    • Modular Neurocontroller for a Sensor-Driven Reactive Behavior of Biologically Inspired Walking Machines 

      Manoonpong, Poramate; Pasemann, Frank; Roth, Hubert (BrSTU, 2006)
      In this article, a modular neurocontroller is presented. It has the capability to generate a reactive behavior of walking machines. The neurocontroller is formed on the basis of a modular structure. It consists of the three different functionality modules: neural preprocessing, a neural oscillator ...

      2023-11-29

    • 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

    • Modular Connectionist Systems: Toward Higher Level Intelligent Functions 

      Kurosh Madani (BrSTU, 2006)
      Recent advances in “neurobiology" allowed highlighting some of key mechanisms of animal intelligence. Among them one can emphasizes brain’s “modular" structure and its ".self-organizing” capabilities. The main goal of this paper is to show how these primary supplies could be exploited and combined in ...

      2023-11-29

    • 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

    • Fusion of Detectors on the Basis of Recirculation Neural Networks for Intrusion Detection 

      Kochurko, Pavel (BrSTU, 2006)
      The identification of attack class plays great role in intrusion detection. In this paper the method of recognition of a class of attack by means of the cumulative classifier with nonlinear recirculation neural networks as private detectors is described, strategy of detector selection – by a relative ...

      2023-11-29

    • Computer-aided technique for defect and project rules inspection on PCB layout image 

      Doudkin, Alexander; Inyutin, Alexander (BrSTU, 2006)
      A technique o f PCB layout optical inspection based on image comparison and mathematical morphology methods is proposed. The unique feature of the technique is that the inspection is performed at different stages of image processing. The presence of all layout elements is checked up, then positions ...

      2023-11-28

    • 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

    • How Many Parachutists will be Needed to Find a Needle in a Pastoral? 

      Akira Imada (BrSTU, 2006)
      This article is a consideration on computer network intrusion detection using artificial neural networks, or whatever else using machine learning techniques. We assume an intrusion to a network is like a needle in a haystack not like a family of iris flower, and we consider how an attack can be detected ...

      2023-11-29

    • 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

    • 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

    • A Fuzzy-CMAC Based Hybrid Intuitive Approach for Biped Robot’s Adaptive Dynamic Walking 

      Sabourin, Christophe; Kurosh Madani; Bruneau, Olivier (BrSTU, 2006)
      In this paper, we have proposed a new neural network based hybrid intuitive approach for biped robot's adaptive walking. Our approach takes advantage on the one hand from a Fuzzy-CMAC based stage and on the other hand from high level intuitive control strategy involving only the regulation of the ...

      2023-11-28

    • 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

    • 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

    • A Steganographic Method Using Learning Vector Quantization 

      Gorbashkо, Larisa; Golovko, Vladimir (BrSTU, 2006)
      The new technique for embedding image data is presented. The message is subjects to vector quantizer by neural network. The modified data is inserted into the coiner in the wavelet transform domain. The vector quantization enables to increase the capacity of embedded data. The experimental results ...

      2023-11-29

    • 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

    • 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

    • 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

    • Simulation Modelling of Neural Control System for Coal Mine Ventilation 

      Turchenko, Iryna; Kochan, VoIodymyr; Sachenko, Anatoly (BrSTU, 2006)
      In this paper it is developed simple simulation model of a mine section in order to model sequential neural control scheme of the mine airflow. A technique of neural network's training set forming, neural network structure and a training algorithm are described. The results of simulation modeling of ...

      2023-11-28

    • An Artificial Neural Network Based Approach to Mass Biometry Dilemma Taking advantage from IBM ZISC-036 Neuro-Processor Based Massively Parallel Implementation 

      Kurosh Madani; Abdennasser Chebira; Damien Langlois (BrSTU, 2006)
      Over the recent past years, new public security tendency to fit up public areas with biometric devices has emerged new requirements in biometric recognition dealing with what we call here "mass biometry". Ifthe main goal in "individual biometry" is to authenticate and/or identify an undesired individual ...

      2023-11-28