Inicio > > Ciencias de la computación > Inteligencia artificial > Redes neuronales y sistemas difusos > Neural Networks and Fuzzy Logic
Neural Networks and Fuzzy Logic

Neural Networks and Fuzzy Logic

Neural Networks and Fuzzy Logic

C Naga Bhaskar / G Vijay Kumar

70,67 €
IVA incluido
Disponible
Editorial:
BS Publications
Año de edición:
2015
Materia
Redes neuronales y sistemas difusos
ISBN:
9789385433238
70,67 €
IVA incluido
Disponible

Selecciona una librería:

  • Librería Samer Atenea
  • Librería Aciertas (Toledo)
  • Kálamo Books
  • Librería Perelló (Valencia)
  • Librería Elías (Asturias)
  • Donde los libros
  • Librería Kolima (Madrid)
  • Librería Proteo (Málaga)
Sobre IBD

This book gives a systemic account of major concepts, methodologies of artificial neural networks and to present a unified frame work that makes the subject more accessible to students and practitioners. The book emphasizes fundamental theoretical aspects of the computational capabilities and learning abilities of artificial neural networks. It integrates important theoretical results on artificial neural networks and uses them to explain a wide range of existing empirical observations and commonly used heuristics. The main audience of the book is undergraduate students in electrical engineering, computer science and engineering. It can also be used as a valuable resource for practical engineering, computer scientists and others involved in research of artificial neural networks 3

Artículos relacionados

  • ANALYSIS & VISUALIZATION DISCRETE DATA USING NEURAL NETWORKS
    KOJI KOYAMADA / KOYAMADA KOJI
    This book serves as a comprehensive step-by-step guide on data analysis and statistical analysis. It covers fundamental operations in Excel, such as table components, formula bar, and ribbon, and introduces visualization techniques and PDE derivation using Excel. It also provides an overview of Google Colab, including code and text cells, and explores visualization and deep lea...
  • GEOMETRIC LINEAR ALGEBRA (V1)
    I-HSIUNG LIN / LIN I-HSIUNG
    This accessible book for beginners uses intuitive geometric concepts to create abstract algebraic theory with a special emphasis on geometric characterizations. The book applies known results to describe various geometries and their invariants, and presents problems concerned with linear algebra, such as in real and complex analysis, differential equations, differentiable manif...
  • GEOMETRIC LINEAR ALGEBRA (V1)
    I-HSIUNG LIN / LIN I-HSIUNG
    This accessible book for beginners uses intuitive geometric concepts to create abstract algebraic theory with a special emphasis on geometric characterizations. The book applies known results to describe various geometries and their invariants, and presents problems concerned with linear algebra, such as in real and complex analysis, differential equations, differentiable manif...
    Disponible

    95,17 €

  • SYNESTHESIA DECODES INNOVATION
    DINGPING (FRANK) QIAN / QIAN DINGPING (FRANK)
    The process of decrypting innovation and creation, as a lurking nondescript so far, is theorized and operationalized based upon interdisciplinary taskings.First comes the mapping between real world and human brain; innovation is redefined as discovering new interrelationships in the brain using an algorithm, well-defined in 5 steps, of searching unknown relations herein, and th...
  • AI-Assisted Programming for Web and Machine Learning
    Anjali Jain / Christoffer Noring / Marina Fernandez
    Speed up your development processes and improve your productivity by writing practical and relevant prompts to build web applications and Machine Learning (ML) modelsPurchase of the print or Kindle book includes a free PDF copyKey Features:- Utilize prompts to enhance frontend and backend web development- Develop prompt strategies to build robust machine learning models- Use Gi...
    Disponible

    72,03 €

  • An Information-Theoretic Approach to Neural Computing
    Dragan Obradovic / Gustavo Deco
    A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design theory of neural networks. In particular they demonstrate how these methods may be applied to the topics of supervised and unsupervised learning, including feature extraction, linear and non-li...