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Computational Intelligence and Bioinspired Systems

8th International Work-Conference on Artificial Neural Networks, IWANN 2005, Vilanova i la Geltrú, Barcelona, Spain, June 8-10, 2005, Proceedings

  • Conference proceedings
  • © 2005

Overview

Editors:
  1. Joan Cabestany

    1. Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Barcelona, Spain

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  2. Alberto Prieto

    1. Department of Computer Architecture and Computer Technology, University of Granada,  

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  3. Francisco Sandoval

    1. Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Málaga, Spain

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3512)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: IWANN 2005.

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Table of contents (153 papers)

  1. Front Matter

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  2. Mathematical and Theoretical Methods

    1. Role of Function Complexity and Network Size in the Generalization Ability of Feedforward Networks

      • Leonardo Franco, José M. Jerez, José M. Bravo
      Pages 1-8

    2. Analysis of the Sanger Hebbian Neural Network

      • J. Andrés Berzal, Pedro J. Zufiria
      Pages 9-16

    3. Considering Multidimensional Information Through Vector Neural Networks

      • J. L. Crespo, R. J. Duro
      Pages 17-24

    4. Combining Ant Colony Optimization with Dynamic Programming for Solving the k-Cardinality Tree Problem

      • Christian Blum, Maria Blesa
      Pages 25-33

  3. Evolutionary Computation

    1. A Basic Approach to Reduce the Complexity of a Self-generated Fuzzy Rule-Table for Function Approximation by Use of Symbolic Interpolation

      • G. Rubio, H. Pomares
      Pages 34-41

    2. Average Time Complexity of Estimation of Distribution Algorithms

      • C. González, A. Ramírez, J. A. Lozano, P. Larrañaga
      Pages 42-49

    3. A Comparison of Evolutionary Approaches to the Shortest Common Supersequence Problem

      • Carlos Cotta
      Pages 50-58

    4. Simultaneous Evolution of Neural Network Topologies and Weights for Classification and Regression

      • Miguel Rocha, Paulo Cortez, José Neves
      Pages 59-66

    5. Applying Bio-inspired Techniques to the p-Median Problem

      • E. Domínguez, J. Muñoz
      Pages 67-74

    6. Optimal Strategy for Resource Allocation of Two-Dimensional Potts Model Using Genetic Algorithm

      • Wing Keung Cheung, Kwok Yip Szeto
      Pages 75-82

    7. Memetic Algorithms to Product-Unit Neural Networks for Regression

      • Francisco Martínez-Estudillo, César Hervás-Martínez, Alfonso Martínez-Estudillo, Domingo Ortíz-Boyer
      Pages 83-90

    8. Lamarckian Clonal Selection Algorithm Based Function Optimization

      • Wuhong He, Haifeng Du, Licheng Jiao, Jing Li
      Pages 91-98

  4. Neurocomputational Inspired Models

    1. Artificial Neural Networks Based on Brain Circuits Behaviour and Genetic Algorithms

      • Ana Porto, Alejandro Pazos, Alfonso Araque
      Pages 99-106

    2. Modeling Synaptic Transmission and Quantifying Information Transfer in the Granular Layer of the Cerebellum

      • Egidio D’Angelo, Thierry Nieus, Michele Bezzi, Angelo Arleo, Olivier J. -M. D. Coenen
      Pages 107-114

    3. The After-Hyperpolarization Amplitude and the Rise Time Constant of IPSC Affect the Synchronization Properties of Networks of Inhibitory Interneurons

      • Angelo Di Garbo, Alessandro Panarese, Michele Barbi, Santi Chillemi
      Pages 115-121

    4. TiViPE Simulation of a Cortical Crossing Cell Model

      • Tino Lourens, Emilia Barakova
      Pages 122-129

    5. A Model of Spiking-Bursting Neuronal Behavior Using a Piecewise Linear Two-Dimensional Map

      • Carlos Aguirre, Doris Campos, Pedro Pascual, Eduardo Serrano
      Pages 130-135

    6. Real-Time Spiking Neural Network: An Adaptive Cerebellar Model

      • Christian Boucheny, Richard Carrillo, Eduardo Ros, Olivier J. -M. D. Coenen
      Pages 136-144

    7. Modeling Neural Processes in Lindenmayer Systems

      • Carlos Martín-Vide, Tseren-Onolt Ishdorj
      Pages 145-152
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Keywords

About this book

We present in this volume the collection of finally accepted papers of the eighth edition of the “IWANN” conference (“International Work-Conference on Artificial Neural Networks”). This biennial meeting focuses on the foundations, theory, models and applications of systems inspired by nature (neural networks, fuzzy logic and evolutionary systems). Since the first edition of IWANN in Granada (LNCS 540, 1991), the Artificial Neural Network (ANN) community, and the domain itself, have matured and evolved. Under the ANN banner we find a very heterogeneous scenario with a main interest and objective: to better understand nature and beings for the correct elaboration of theories, models and new algorithms. For scientists, engineers and professionals working in the area, this is a very good way to get solid and competitive applications. We are facing a real revolution with the emergence of embedded intelligence in many artificial systems (systems covering diverse fields: industry, domotics, leisure, healthcare, … ). So we are convinced that an enormous amount of work must be, and should be, still done. Many pieces of the puzzle must be built and placed into their proper positions, offering us new and solid theories and models (necessary tools) for the application and praxis of these current paradigms. The above-mentioned concepts were the main reason for the subtitle of the IWANN 2005 edition: “Computational Intelligence and Bioinspired Systems.” The call for papers was launched several months ago, addressing the following topics: 1. Mathematical and theoretical methods in computational intelligence.

Editors and Affiliations

  • Departamento de Ingeniería Electrónica, Universitat Politècnica de Catalunya (UPC). E.T.S.I. de Telecomunicación, Barcelona, Spain

    Joan Cabestany

  • Department of Computer Architecture and Computer Technology, University of Granada,  

    Alberto Prieto

  • Grupo ISIS, Dpto. Tecnología Electrónica ETSI Telecomunicación, Universidad de Málaga, Málaga, Spain

    Francisco Sandoval

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