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Artificial Neural Networks and Machine Learning -- ICANN 2012

22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part I

  • Conference proceedings
  • © 2012

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Editors:
  1. Alessandro E. P. Villa

    1. Neuro Heuristic Research Group, University of Lausanne, Lausanne, Switzerland

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  2. Włodzisław Duch

    1. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

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  3. Péter Érdi

    1. Center for Complex Systems Studies, Kalamazoo College, Kalamazoo, USA

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  4. Francesco Masulli

    1. Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, Genoa, Italy

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  5. Günther Palm

    1. Institut für Neuroinformatik, Universität Ulm, Ulm, Germany

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  • Up-to-date results Fast-track conference proceedings
  • State-of-the-art research

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7552)

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

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Conference proceedings info: ICANN 2012.

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About this book

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

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Keywords

Table of contents (91 papers)

  1. Front Matter

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  2. Theoretical Neural Computation (A3)

    1. Temporal Patterns in Artificial Reaction Networks

      • Claire Gerrard, John McCall, George M. Coghill, Christopher Macleod
      Pages 1-8

    2. Properties of the Hopfield Model with Weighted Patterns

      • Iakov Karandashev, Boris Kryzhanovsky, Leonid Litinskii
      Pages 9-16

    3. Dynamics and Oscillations of GHNNs with Time-Varying Delay

      • Farouk Chérif
      Pages 17-24

    4. A Dynamic Field Architecture for the Generation of Hierarchically Organized Sequences

      • Boris Durán, Yulia Sandamirskaya, Gregor Schöner
      Pages 25-32

  3. Information and Optimization (C1)

    1. Stochastic Techniques in Influence Diagrams for Learning Bayesian Network Structure

      • Michal Matuszak, Jacek Miękisz
      Pages 33-40

    2. The Mix-Matrix Method in the Problem of Binary Quadratic Optimization

      • Iakov Karandashev, Boris Kryzhanovsky
      Pages 41-48

    3. A Rule Chaining Architecture Using a Correlation Matrix Memory

      • James Austin, Stephen Hobson, Nathan Burles, Simon O’Keefe
      Pages 49-56

    4. A Generative Multiset Kernel for Structured Data

      • Davide Bacciu, Alessio Micheli, Alessandro Sperduti
      Pages 57-64

    5. Spectral Signal Unmixing with Interior-Point Nonnegative Matrix Factorization

      • Rafal Zdunek
      Pages 65-72

    6. Hybrid Optimized Polynomial Neural Networks with Polynomial Neurons and Fuzzy Polynomial Neurons

      • Dan Wang, Donghong Ji, Wei Huang
      Pages 73-80

    7. Tikhonov-Type Regularization for Restricted Boltzmann Machines

      • KyungHyun Cho, Alexander Ilin, Tapani Raiko
      Pages 81-88

  4. From Neurons to Neuromorphism (A1)

    1. Modeling of Spiking Analog Neural Circuits with Hebbian Learning, Using Amorphous Semiconductor Thin Film Transistors with Silicon Oxide Nitride Semiconductor Split Gates

      • Richard Wood, Ian Bruce, Peter Mascher
      Pages 89-96

    2. Real-Time Simulations of Synchronization in a Conductance-Based Neuronal Network with a Digital FPGA Hardware-Core

      • Marcel Beuler, Aubin Tchaptchet, Werner Bonath, Svetlana Postnova, Hans Albert Braun
      Pages 97-104

    3. Impact of Frequency on the Energetic Efficiency of Action Potentials

      • Anand Singh, Pierre J. Magistretti, Bruno Weber, Renaud Jolivet
      Pages 105-112

    4. A Large-Scale Spiking Neural Network Accelerator for FPGA Systems

      • Kit Cheung, Simon R. Schultz, Wayne Luk
      Pages 113-120

    5. Silicon Neurons That Compute

      • Swadesh Choudhary, Steven Sloan, Sam Fok, Alexander Neckar, Eric Trautmann, Peiran Gao et al.
      Pages 121-128

    6. A Communication Infrastructure for Emulating Large-Scale Neural Networks Models

      • Andres Gaona Barrera, Manuel Moreno Arostegui
      Pages 129-136

  5. Spiking Dynamics (B2)

    1. Pair-Associate Learning with Modulated Spike-Time Dependent Plasticity

      • Nooraini Yusoff, André Grüning, Scott Notley
      Pages 137-144

    2. Associative Memory in Neuronal Networks of Spiking Neurons: Architecture and Storage Analysis

      • Everton J. Agnes, Rubem Erichsen Jr., Leonardo G. Brunnet
      Pages 145-152
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Other volumes

  1. Artificial Neural Networks and Machine Learning – ICANN 2012

  2. Artificial Neural Networks and Machine Learning – ICANN 2012

Editors and Affiliations

  • Neuro Heuristic Research Group, University of Lausanne, Lausanne, Switzerland

    Alessandro E. P. Villa

  • Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  • Center for Complex Systems Studies, Kalamazoo College, Kalamazoo, USA

    Péter Érdi

  • Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, Genoa, Italy

    Francesco Masulli

  • Institut für Neuroinformatik, Universität Ulm, Ulm, Germany

    Günther Palm

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