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  • 1
    UID:
    b3kat_BV043438591
    Format: XVIII, 243 Seiten, [6] Blätter , graph. Darst.
    ISBN: 0471322709 , 9780471322702
    Series Statement: Adaptive and learning systems for signal processing, communication, and control
    Content: "Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Where most books on the subject are dedicated to PCA (principal component analysis) and consider MCA (minor component analysis) as simply a consequence, this is the fist book to start from the MCA problem and arrive at important conclusions about the PCA problem."--
    Note: Literaturverzeichnis S. 227 - 237
    Language: English
    Keywords: Neuronales Netz ; Hauptkomponentenanalyse
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