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Autor(en): 
  • Harish Parthasarathy
  • Applications of Quantum Field Theory to Problems in Machine Learning: Advanced Techniques Based on Path Integrals 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Mai 2026  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Applied physics / COMPUTERS / Data Science / Machine Learning / curved spacetime modelling / Digital and Information technology# general topics / Hamiltonian;Supersymmetric Field Theory;Renormalisation;Scattering;QNN / Information technology# general issues / Neural networks & fuzzy systems / Neural networks and fuzzy systems
    ISBN:  9781041281252 
    EAN-Code: 
    9781041281252 
    Verlag:  Taylor and Francis 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D  
    Gewicht:  890 gr 
    Seiten:  376 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    This book examines quantum neural networks through renormalization techniques, supersymmetric field theory, and noisy harmonic oscillator systems. The book's analysis covers adaptive beamforming applications, brain modeling, gravitational control mechanisms, and mixed-state dynamics in superstring theory, and also includes:

    • Comprehensive analysis of quantum neural networks through renormalization techniques and supersymmetric field theory applications in computational modeling
    • Investigation of quantum field dynamics with noise integration, filtering mechanisms, and scattering processes in curved spacetime environments
    • Study of adaptive beamforming methodologies combined with quantum neural networks for brain modeling and evolving field system applications
    • Examination of mixed-state dynamics in superstring theory frameworks with emphasis on quantum noisy fields and supersymmetric effects
    • Analysis of extended Kalman filter integration with quantum neural networks for transmission line control and field estimation optimization

    The work explores extended Kalman filter methodologies for transmission line control, field estimation, and symmetry-broken dynamics in signal processing systems for advanced computational modeling applications.

    This title has been co-published with Manakin Press. T&F does not sell or distribute the print editions in Bangladesh, Bhutan, India, Nepal, Pakistan, and Sri lanka.

      



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