Bio-Inspired Applications of Connectionism

1. Front Matter

   Pages I-XXVII

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2. Bio-inspired Systems and Engineering

   1. From Embryonics to POEtic Machines

      • Daniel Mange, André Stauffer, Gianluca Tempesti, Christof Teuscher

      Pages 1-13

   2. Design and Codesign of Neuro-fuzzy Hardware

      • L. M. Reyneri

      Pages 14-30

   3. A Field-Programmable Conductance Array IC for Biological Neurons Modeling

      • Vincent Douence, S. Renaud-Le Masson, S. Saïghi, G. Le Masson

      Pages 31-38

   4. A 2-by-n Hybrid Cellular Automaton Implementation Using a Bio-inspired FPGA

      • Hector Fabio Restrepo, Daniel Mange

      Pages 39-46

   5. Parametric Neurocontroller for Positioning of an Anthropomorfic Finger Based on an Oponent Driven-Tendon Transmission System

      • J. I. Mulero, J. Feliú Batlle, J. López Coronado

      Pages 47-54

   6. An Integration Principle for Multimodal Sensor Data Based on Temporal Coherence of Self-Organized Patterns

      • Emilia I. Barakova

      Pages 55-63

   7. Simultaneous Parallel Processing of Object and Position by Temporal Correlation

      • Luis F. Lago-Fernández, Gustavo Deco

      Pages 64-71

3. Methodology for Nets Design, Nets Simulation and Implementation

   1. NeuSim: A Modular Neural Networks Simulator for Beowulf Clusters

      • Carlos J. García Orellana, Ramón Gallardo Caballero, Horacio M. González Velasco, Francisco J. López Aligué

      Pages 72-79

   2. Curved Kernel Neural Network for Functions Approximation

      • Paul Bourret, Bruno Pelletier

      Pages 80-87

   3. Repeated Measures Multiple Comparison Procedures Applied to Model Selection in Neural Networks

      • Elisa Guerrero Vázquez, Andrés Yañez Escolano, Pedro Galindo Riaño, Joaquín Pizarro Junquera

      Pages 88-95

   4. Extension of HUMANN for Dealing with Noise and with Classes of Different Shape and Size: A Parametric Study

      • Patricio García Báez, Carmen Paz Suárez Araujo, Pablo Fernández López

      Pages 96-103

   5. Evenet 2000: Designing and Training Arbitrary Neural Networks in Java

      • Evelio J. González, Alberto F. Hamilton, Lorenzo Moreno, José F. Sigut, Roberto L. Marichal

      Pages 104-110

   6. Neyman-Pearson Neural Detectors

      • Diego Andina, José L. Sanz-González

      Pages 111-118

   7. Distance between Kohonen Classes Visualization Tool to Use SOM in Data Set Analysis and Representation

      • Patrick Rousset, Christiane Guinot

      Pages 119-126

   8. Optimal Genetic Representation of Complete Strictly-Layered Feedforward Neural Networks

      • Spyros Raptis, Spyros Tzafestas, Hermione Karagianni

      Pages 127-135

   9. Assesing the Noise Immunity of Radial Basis Function Neural Networks

      • J. L. Bernier, J. González, A. Cañas, J. Ortega

      Pages 136-143

   10. Analyzing Boltzmann Machine Parameters for Fast Convergence

       • Fco. Javier Salcedo, Julio Ortega, Alberto Prieto

       Pages 144-151

   11. A Penalization Criterion Based on Noise Behaviour for Model Selection

       • JoaquínPizarro Junquera, Pedro Galindo Riaño, Elisa Guerrero Vázquez, Andrés Yañez Escolano1

       Pages 152-159

4. Image Processing

   1. Wood Texture Analysis by Combining the Connected Elements Histogram and Artificial Neural Networks

      • M. A. Patricio Guisado, D. Maravall Gómez-Allende

      Pages 160-167

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.

• Signatur
• artificial intelligence
• artificial neural network
• automata
• cellular automaton
• classification
• data mining
• diagnosis
• evolutionary algorithm
• image analysis
• image processing
• learning theory
• neurons
• robotics
• statistics
• algorithm analysis and problem complexity

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

  José Mira

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

  Alberto Prieto

Policies and ethics