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Advances in Neuromorphic Memristor Science and Applications

ISBN-13: 9789402406153 / Angielski / Miękka / 2016 / 320 str.

Robert Kozma; Robinson E. Pino; Giovanni E. Pazienza
Advances in Neuromorphic Memristor Science and Applications Robert Kozma Robinson E. Pino Giovanni E. Pazienza 9789402406153 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Advances in Neuromorphic Memristor Science and Applications

ISBN-13: 9789402406153 / Angielski / Miękka / 2016 / 320 str.

Robert Kozma; Robinson E. Pino; Giovanni E. Pazienza
cena 806,99 zł
(netto: 768,56 VAT:  5%)

Najniższa cena z 30 dni: 771,08 zł
Termin realizacji zamówienia:
ok. 22 dni roboczych
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Kategorie:
Nauka, Medycyna
Kategorie BISAC:
Medical > Neuroscience
Computers > Artificial Intelligence - General
Science > Nanoscience
Wydawca:
Springer
Seria wydawnicza:
Springer Series in Cognitive and Neural Systems
Język:
Angielski
ISBN-13:
9789402406153
Rok wydania:
2016
Wydanie:
Softcover Repri
Ilość stron:
320
Oprawa:
Miękka
Wolumenów:
01

Foreword

Part I  Fundamental Concepts of Memristors and Neuromorphic Systems  

Prolog – Memristor Minds; Greg Snider

  1. Are Memristors the Future of AI? – A Review of Recent Progress and Future Perspectives; Robert Kozma, Robinson E. Pino, and Giovanni E. Pazienza  
  2. Biologically-Inspired Electronics with Memory Circuit Elements; Massimiliano Di Ventra and Yuriy Pershin 
  3. Persuading Computers to Act More Like Brains; Heather Ames, Massimiliano Versace, Anatoli Gorchetchnikov, Benjamin Chandler, Gennady Livitz, Jasmin Léveillé, Ennio Mingolla, Dick Carter, Hisham Abdalla, and Greg Snider 
  4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications; Paul J. Werbos 

Part II  Computational Models of Memristors

  1. Computational Intelligence and Neuromorphic Computing Architectures; Robinson E. Pino 
  2. Reconfigurable Memristor Fabrics for Heterogeneous Computing; Dhireesha Kudithipudi and Cory E. Merkel  
  3. Statistical Memristor Model and Its Applications in Neuromorphic Computing; Hai (Helen) Li and Pino E. Robinson 
  4. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware; Max Versace, Robert T. Kozma, and Donald C. Wunsch 
  5. Memristor SPICE Modeling; Chris Yakopcic, Tarek M. Taha, Guru Subramanyam, and Robinson E. Pino  

Part III. Hardware Embodiments with Memristive Properties and Applications

  1. Energy-Efficient Memristive Analog and Digital Electronics; Sung Mo “Steve” Kang and Sangho Shin 
  2. Memristor Models for Pattern Recognition Systems; Fernando Corinto, A. Ascoli, and Marco Gilli 
  3. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity; Manan Suri, and Barbara DeSalvo
  4. A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  5.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 
  6. Index

    A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  7.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 

Index

Prolog – Memristor Minds; Greg Snider

  1. Are Memristors the Future of AI? – A Review of Recent Progress and Future Perspectives; Robert Kozma, Robinson E. Pino, and Giovanni E. Pazienza  
  2. Biologically-Inspired Electronics with Memory Circuit Elements; Massimiliano Di Ventra and Yuriy Pershin 
  3. Persuading Computers to Act More Like Brains; Heather Ames, Massimiliano Versace, Anatoli Gorchetchnikov, Benjamin Chandler, Gennady Livitz, Jasmin Léveillé, Ennio Mingolla, Dick Carter, Hisham Abdalla, and Greg Snider 
  4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications; Paul J. Werbos 

Part II  Computational Models of Memristors

  1. Computational Intelligence and Neuromorphic Computing Architectures; Robinson E. Pino 
  2. Reconfigurable Memristor Fabrics for Heterogeneous Computing; Dhireesha Kudithipudi and Cory E. Merkel  
  3. Statistical Memristor Model and Its Applications in Neuromorphic Computing; Hai (Helen) Li and Pino E. Robinson 
  4. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware; Max Versace, Robert T. Kozma, and Donald C. Wunsch 
  5. Memristor SPICE Modeling; Chris Yakopcic, Tarek M. Taha, Guru Subramanyam, and Robinson E. Pino  

Part III. Hardware Embodiments with Memristive Properties and Applications

  1. Energy-Efficient Memristive Analog and Digital Electronics; Sung Mo “Steve” Kang and Sangho Shin 
  2. Memristor Models for Pattern Recognition Systems; Fernando Corinto, A. Ascoli, and Marco Gilli 
  3. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity; Manan Suri, and Barbara DeSalvo
  4. A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  5.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 
  6. Index

    A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  7.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 

Index

Part I  Fundamental Concepts of Memristors and Neuromorphic Systems  

Prolog – Memristor Minds; Greg Snider

  1. Are Memristors the Future of AI? – A Review of Recent Progress and Future Perspectives; Robert Kozma, Robinson E. Pino, and Giovanni E. Pazienza  
  2. Biologically-Inspired Electronics with Memory Circuit Elements; Massimiliano Di Ventra and Yuriy Pershin 
  3. Persuading Computers to Act More Like Brains; Heather Ames, Massimiliano Versace, Anatoli Gorchetchnikov, Benjamin Chandler, Gennady Livitz, Jasmin Léveillé, Ennio Mingolla, Dick Carter, Hisham Abdalla, and Greg Snider 
  4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications; Paul J. Werbos 

Part II  Computational Models of Memristors

  1. Computational Intelligence and Neuromorphic Computing Architectures; Robinson E. Pino 
  2. Reconfigurable Memristor Fabrics for Heterogeneous Computing; Dhireesha Kudithipudi and Cory E. Merkel  
  3. Statistical Memristor Model and Its Applications in Neuromorphic Computing; Hai (Helen) Li and Pino E. Robinson 
  4. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware; Max Versace, Robert T. Kozma, and Donald C. Wunsch 
  5. Memristor SPICE Modeling; Chris Yakopcic, Tarek M. Taha, Guru Subramanyam, and Robinson E. Pino  

Part III. Hardware Embodiments with Memristive Properties and Applications

  1. Energy-Efficient Memristive Analog and Digital Electronics; Sung Mo “Steve” Kang and Sangho Shin 
  2. Memristor Models for Pattern Recognition Systems; Fernando Corinto, A. Ascoli, and Marco Gilli 
  3. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity; Manan Suri, and Barbara DeSalvo
  4. A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  5.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 
  6. Index

    A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  7.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 

Index

Prolog – Memristor Minds; Greg Snider

  1. Are Memristors the Future of AI? – A Review of Recent Progress and Future Perspectives; Robert Kozma, Robinson E. Pino, and Giovanni E. Pazienza  
  2. Biologically-Inspired Electronics with Memory Circuit Elements; Massimiliano Di Ventra and Yuriy Pershin 
  3. Persuading Computers to Act More Like Brains; Heather Ames, Massimiliano Versace, Anatoli Gorchetchnikov, Benjamin Chandler, Gennady Livitz, Jasmin Léveillé, Ennio Mingolla, Dick Carter, Hisham Abdalla, and Greg Snider 
  4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications; Paul J. Werbos 

Part II  Computational Models of Memristors

  1. Computational Intelligence and Neuromorphic Computing Architectures; Robinson E. Pino 
  2. Reconfigurable Memristor Fabrics for Heterogeneous Computing; Dhireesha Kudithipudi and Cory E. Merkel  
  3. Statistical Memristor Model and Its Applications in Neuromorphic Computing; Hai (Helen) Li and Pino E. Robinson 
  4. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware; Max Versace, Robert T. Kozma, and Donald C. Wunsch 
  5. Memristor SPICE Modeling; Chris Yakopcic, Tarek M. Taha, Guru Subramanyam, and Robinson E. Pino  

Part III. Hardware Embodiments with Memristive Properties and Applications

  1. Energy-Efficient Memristive Analog and Digital Electronics; Sung Mo “Steve” Kang and Sangho Shin 
  2. Memristor Models for Pattern Recognition Systems; Fernando Corinto, A. Ascoli, and Marco Gilli 
  3. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity; Manan Suri, and Barbara DeSalvo
  4. A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  5.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 
  6. Index

    A Columnar V1/V2 Visual Cortex Model and Emulation; Robinson E. Pino and Michael Moore 
  7.   Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications
    Robert A. Nawrocki, Richard M. Voyles, and Sean E. Shaeen 

Posited by Professor Leon Chua at UC Berkeley more than 40 years ago, memristors, a nonlinear element in electrical circuitry, are set to revolutionize computing technology. Finally discovered by scientists at Hewlett-Packard in 2008, memristors  generate huge interest because they can facilitate nanoscale, real-time computer learning, as well as due to their potential of serving as instant memories. . This edited volume bottles some of the excitement about memristors, providing a state-of-the-art overview of neuromorphic memristor theory, as well as its technological and practical aspects.

Based on work presented to specialist memristor seminars organized by the editors, the volume takes readers from a general introduction the fundamental concepts involved, to specialized analysis of computational modeling, hardware, and applications. The latter include the ground-breaking potential of memristors in facilitating hybrid wetware-hardware technologies for in-vitro experiments. The book evinces, and devotes space to the discussion of, the socially transformative potential of memristors, which could be as pervasive as was the invention of the silicon chip: machines that learn in the style of brains, are a computational Holy Grail.

With contributions from key players in a fast-moving field, this edited volume is the first to cover memristors in the depth needed to trigger the further advances that surely lie around the corner.

Kozma, Robert Kozma is a Principal Scientist and Fulbright Senio... więcej >


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