Advances in Neuromorphic Memristor Science and Applications

1. Front Matter

   Pages 1-1

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2. Fundamental Concepts of Memristors and Neuromorphic Systems

   1. Front Matter

      Pages 1-1

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   2. Prolog: Memristor Minds

      • Greg Snider

      Pages 3-7

   3. Are Memristors the Future of AI?

      • Robert Kozma, Robinson E. Pino, Giovanni E. Pazienza

      Pages 9-14

   4. Biologically-Inspired Electronics with Memory Circuit Elements

      • Massimiliano Di Ventra, Yuriy V. Pershin

      Pages 15-36

   5. Persuading Computers to Act More Like Brains

      • Heather Ames, Massimiliano Versace, Anatoli Gorchetchnikov, Benjamin Chandler, Gennady Livitz, Jasmin Léveillé et al.

      Pages 37-61

   6. Memristors for More Than Just Memory: How to Use Learning to Expand Applications

      • Paul J. Werbos

      Pages 63-73

3. Computational Models of Memristors

   1. Front Matter

      Pages 75-75

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   2. Computational Intelligence and Neuromorphic Computing Architectures

      • Robinson E. Pino

      Pages 77-88

   3. Reconfigurable Memristor Fabrics for Heterogeneous Computing

      • Dhireesha Kudithipudi, Cory E. Merkel

      Pages 89-106

   4. Statistical Memristor Model and Its Applications in Neuromorphic Computing

      • Hai Helen Li, Miao Hu, Robinson E. Pino

      Pages 107-131

   5. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware

      • Max Versace, Robert T. Kozma, Donald C. Wunsch

      Pages 133-153

   6. Phase Change Memory and Chalcogenide Materials for Neuromorphic Applications: Emphasis on Synaptic Plasticity

      • Manan Suri, Barbara DeSalvo

      Pages 155-178

4. Hardware Embodiments with Memristive Properties and Applications

   1. Front Matter

      Pages 179-179

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   2. Energy-Efficient Memristive Analog and Digital Electronics

      • Sung Mo Steve Kang, Sangho Shin

      Pages 181-209

   3. Memristor SPICE Modeling

      • Chris Yakopcic, Tarek M. Taha, Guru Subramanyam, Robinson E. Pino

      Pages 211-244

   4. Memristor Models for Pattern Recognition Systems

      • Fernando Corinto, Alon Ascoli, Marco Gilli

      Pages 245-267

   5. A Columnar V1/V2 Visual Cortex Model and Emulation

      • Robinson E. Pino, Michael Moore

      Pages 269-290

   6. Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications

      • Robert A. Nawrocki, Richard M. Voyles, Sean E. Shaheen

      Pages 291-314

5. Back Matter

   Pages 306-306

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Physical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent robotics. As any promising new technology, it has raised hopes and questions; it is an extremely challenging task to live up to the high expectations and to devise revolutionary and feasible future applications for memristive devices. The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future perspectives in neuromorphic memristor science. This book presents a selection of the remarkable contributions given by the leaders of the field and it may serve as inspiration and future reference to all researchers that want to explore the extraordinary possibilities given bythis revolutionary concept.

• Cellular Network
• Memristor
• Nanotechnology
• Neural Network
• Neuromorphic Architecture

• Dept. Mathematical Sciences, University of Memphis, Memphis, USA

  Robert Kozma

• , RITC, Information Directorate, Air Force Research Laboratory, Rome, USA

  Robinson E. Pino

• , Mathematical Sciences, The University of Memphis, Memphis, USA

  Giovanni E. Pazienza

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