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Autor(en): 
  • Enrique Castillo
  • Angel Cobo
  • Jose Antonio Gutierrez
  • Rosa Eva Pruneda
  • Functional Networks with Applications: A Neural-Based Paradigm 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Februar 2013  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Algorithms / Architecture / ArtificialIntelligence / Computer-Aided Design (CAD) / computer-aideddesign(CAD) / computerscience / Consumption / dataanalysis
    ISBN:  9781461375623 
    EAN-Code: 
    9781461375623 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 18 mm 
    Gewicht:  493 gr 
    Seiten:  324 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book introduces `functional networks', a novel neural-based paradigm, and shows that functional network architectures can be efficiently applied to solve many interesting practical problems. Included is an introduction to neural networks, a description of functional networks, examples of applications, and computer programs in Mathematica and Java languages implementing the various algorithms and methodologies. Special emphasis is given to applications in several areas such as:
    • Box-Jenkins AR(p), MA(q), ARMA(p,q), and ARIMA (p,d,q) models with application to real-life economic problems such as the consumer price index, electric power consumption and international airlines' passenger data. Random time series and chaotic series are considered in relation to the Hénon, Lozi, Holmes and Burger maps, as well as the problems of noise reduction and information masking.
    • Learning differential equations from data and deriving the corresponding equivalent difference and functional equations. Examples of a mass supported by two springs and a viscous damper or dashpot, and a loaded beam, are used to illustrate the concepts.
    • The problem of obtaining the most general family of implicit, explicit and parametric surfaces as used in Computer Aided Design (CAD).
    • Applications of functional networks to obtain general nonlinear regression models are given and compared with standard techniques.
    Functional Networks with Applications: A Neural-Based Paradigm will be of interest to individuals who work in computer science, physics, engineering, applied mathematics, statistics, economics, and other neural networks and data analysis related fields.

      



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