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  • Conference proceedings
  • © 2001

Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence

6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2084)

Conference series link(s): IWANN: International Work-Conference on Artificial Neural Networks

Conference proceedings info: IWANN 2001.

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Table of contents (99 papers)

  1. Front Matter

    Pages I-XXVII
  2. Foundations of Connectionism and Biophysical Models of Neurons

    1. Dendrites: The Last-Generation Computers

      • O. Herreras, J. M. Ibarz, L. López-Aguado, P. Varona
      Pages 1-13
    2. A Realistic Computational Model of the Local Circuitry of the Cuneate Nucleus

      • Eduardo Sroseanchez, Senrosesen Barro, Jorge Mariño, Antonio Canedo
      Pages 21-29
    3. What Can We Compute with Lateral Inhibition Circuits?

      • Josrosee Mira, Ana E. Delgado
      Pages 38-46
    4. Neuronal Models with Current Inputs

      • Jianfeng Fent
      Pages 47-54
    5. Decoding the Population Responses of Retinal Ganglions Cells Using Information Theory

      • J. M. Ferrández, M. Bongard, F. García de Quiros, J. A. Bolea, J. Ammermü, R. A. Normann et al.
      Pages 55-62
    6. Neurobiological Modeling of Bursting Response During Visual Attention

      • Reza Rajimehr, Leila Montaser Kouhsari
      Pages 72-80
    7. Synchronisation Mechanisms in Neuronal Networks

      • Santi Chillemi, Michele Barbi, Angelo Di Garbo
      Pages 87-94
    8. Detection of Oriented Repetitive Alternating Patterns in color Images

      • Tino Lourens, Hiroshi G. Okuno, Hiroaki Kitano
      Pages 95-107
    9. Synchronization in Brain — Assessment by Electroencephalographic Signals

      • Ernesto Pereda, Joydeep Bhattacharya
      Pages 108-116
  3. Structural and Functional Models of Neurons

    1. Verifying Properties of Neural Networks

      • Pedro Rodrigues, J. Félix Costa, Hava T. Siegelmann
      Pages 158-165

Other Volumes

  1. Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence

    6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001 Proceedings, Part 1
  2. Bio-Inspired Applications of Connectionism

    6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001 Proceedings, Part II

About this book

Underlying most of the IWANN calls for papers is the aim to reassume some of the motivations of the groundwork stages of biocybernetics and the later bionics formulations and to try to reconsider the present value of two basic questions. The?rstoneis:“Whatdoesneurosciencebringintocomputation(thenew bionics)?” That is to say, how can we seek inspiration in biology? Titles such as “computational intelligence”, “arti?cial neural nets”, “genetic algorithms”, “evolutionary hardware”, “evolutive architectures”, “embryonics”, “sensory n- romorphic systems”, and “emotional robotics” are representatives of the present interest in “biological electronics” (bionics). Thesecondquestionis:“Whatcanreturncomputationtoneuroscience(the new neurocybernetics)?” That is to say, how can mathematics, electronics, c- puter science, and arti?cial intelligence help the neurobiologists to improve their experimental data modeling and to move a step forward towards the understa- ing of the nervous system? Relevant here are the general philosophy of the IWANN conferences, the sustained interdisciplinary approach, and the global strategy, again and again to bring together physiologists and computer experts to consider the common and pertinent questions and the shared methods to answer these questions.

Keywords

  • Connectionism
  • Simulation
  • algorithmic learning
  • artificial neural networks
  • biocomputing
  • brain-like computations
  • evolutionary algorithms
  • genetic algorithms
  • heuristics
  • knowledge
  • multi-objective optimization
  • neurons
  • reinforcement learning
  • robot
  • statistics
  • algorithm analysis and problem complexity

Editors and Affiliations

  • Departamento de Inteligencia Artificial Sanda del Rey, Universidad Nacional de Educación a Distancia, Madrid, Spain

    José Mira

  • Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada, Granada, Spain

    Alberto Prieto

Bibliographic Information

Buying options

eBook
USD 109.00
Price excludes VAT (USA)
  • ISBN: 978-3-540-45720-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD 149.99
Price excludes VAT (USA)