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Wyszukujesz frazę "feature-based optimization" wg kryterium: Temat

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    Wyświetlanie 1-3 z 3
    Tytuł:
    Rapid Design Optimization of Multi-Band Antennas by Means of Response Features
    Autorzy:
    Kozieł, S.
    Bekasiewicz, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/221503.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    antenna design
    antenna measurements
    computer-aided design
    surrogate modelling
    feature-based optimization
    Opis:
    This work examines the reduced-cost design optimization of dual- and multi-band antennas. The primary challenge is independent yet simultaneous control of the antenna responses at two or more frequency bands. In order to handle this task, a feature-based optimization approach is adopted where the design objectives are formulated on the basis of the coordinates of so-called characteristic points (or response features) of the antenna response. Due to only slightly nonlinear dependence of the feature points on antenna geometry parameters, optimization can be attained at a low computational cost. Our approach is demonstrated using two antenna structures with the optimum designs obtained in just a few dozen of EM simulations of the respective structure.
    Źródło:
    Metrology and Measurement Systems; 2017, 24, 2; 337-346
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multi-objective heuristic feature selection for speech-based multilingual emotion recognition
    Autorzy:
    Brester, C.
    Semenkin, E.
    Sidorov, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/91588.pdf
    Data publikacji:
    2016
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    multi-objective optimization
    feature selection
    speech-based emotion recognition
    Opis:
    If conventional feature selection methods do not show sufficient effectiveness, alternative algorithmic schemes might be used. In this paper we propose an evolutionary feature selection technique based on the two-criterion optimization model. To diminish the drawbacks of genetic algorithms, which are applied as optimizers, we design a parallel multicriteria heuristic procedure based on an island model. The performance of the proposed approach was investigated on the Speech-based Emotion Recognition Problem, which reflects one of the most essential points in the sphere of human-machine communications. A number of multilingual corpora (German, English and Japanese) were involved in the experiments. According to the results obtained, a high level of emotion recognition was achieved (up to a 12.97% relative improvement compared with the best F-score value on the full set of attributes).
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 4; 243-253
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Similarity-based methods : a general framework for classification, approximation and association
    Autorzy:
    Duch, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/206007.pdf
    Data publikacji:
    2000
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    aproksymacja
    klasyfikacja
    optymalizacja
    pamięć asocjacyjna
    approximation
    associative memory
    classification
    feature selection
    kNN
    optimization
    similarity-based methods
    Opis:
    Similarity-based methods (SBM) are a generalization of the minimal distance (MD) methods which form a basis of several machine learning and pattern recognition methods. Investigation of similarity leads to a fruitful framework in which many classification, approximation and association methods are accommodated. Probability p(C|X; M) of assigning class C to a vector X, given a classification model M, depends on adaptive parameters and procedures used in construction of the model. Systematic overview of choices available for model building is presented and numerous improvements suggested. Similarity-Based Methods have natural neural-network type realizations. Such neural network models as the Radial Basis Functions (RBF) and the Multilayer Perceptrons (MLPs) are included in this framework as special cases. SBM may also include several different submodels and a procedure to combine their results. Many new versions of similarity-based methods are derived from this framework. A search in the space of all methods belonging to the SBM framework finds a particular combination of parameterizations and procedures that is most appropriate for a given data. No single classification method can beat this approach. Preliminary implementation of SBM elements tested on a real-world datasets gave very good results.
    Źródło:
    Control and Cybernetics; 2000, 29, 4; 937-967
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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