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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…mehr
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.
Part I Fundamental Concepts of Memristors and Neuromorphic Systems. - Prolog ? Memristor Minds. - 1. Are Memristors the Future of AI? ? A Review of Recent Progress and Future Perspectives. - 2. Biologically-Inspired Electronics with Memory Circuit Elements. - 3. Persuading Computers to Act More Like Brains. - 4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications. - Part II Computational Models of Memristors. - 5. Computational Intelligence and Neuromorphic Computing Architectures. - 6. Reconfigurable Memristor Fabrics for Heterogeneous Computing. - 7. Statistical Memristor Model and Its Applications in Neuromorphic Computing. - 8. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware. - 9. Memristor SPICE Modeling. - Part III. Hardware Embodiments with Memristive Properties and Applications. - 10. Energy-Efficient Memristive Analog and Digital Electronics. - 11. Memristor Models for Pattern Recognition Systems. - 12. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity. - 13. A Columnar V1/V2 Visual Cortex Model and Emulation. - 14. Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications.
Part I Fundamental Concepts of Memristors and Neuromorphic Systems. - Prolog ? Memristor Minds. - 1. Are Memristors the Future of AI? ? A Review of Recent Progress and Future Perspectives. - 2. Biologically-Inspired Electronics with Memory Circuit Elements. - 3. Persuading Computers to Act More Like Brains. - 4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications. - Part II Computational Models of Memristors. - 5. Computational Intelligence and Neuromorphic Computing Architectures. - 6. Reconfigurable Memristor Fabrics for Heterogeneous Computing. - 7. Statistical Memristor Model and Its Applications in Neuromorphic Computing. - 8. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware. - 9. Memristor SPICE Modeling. - Part III. Hardware Embodiments with Memristive Properties and Applications. - 10. Energy-Efficient Memristive Analog and Digital Electronics. - 11. Memristor Models for Pattern Recognition Systems. - 12. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity. - 13. A Columnar V1/V2 Visual Cortex Model and Emulation. - 14. Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications.
Part I Fundamental Concepts of Memristors and Neuromorphic Systems. - Prolog ? Memristor Minds. - 1. Are Memristors the Future of AI? ? A Review of Recent Progress and Future Perspectives. - 2. Biologically-Inspired Electronics with Memory Circuit Elements. - 3. Persuading Computers to Act More Like Brains. - 4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications. - Part II Computational Models of Memristors. - 5. Computational Intelligence and Neuromorphic Computing Architectures. - 6. Reconfigurable Memristor Fabrics for Heterogeneous Computing. - 7. Statistical Memristor Model and Its Applications in Neuromorphic Computing. - 8. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware. - 9. Memristor SPICE Modeling. - Part III. Hardware Embodiments with Memristive Properties and Applications. - 10. Energy-Efficient Memristive Analog and Digital Electronics. - 11. Memristor Models for Pattern Recognition Systems. - 12. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity. - 13. A Columnar V1/V2 Visual Cortex Model and Emulation. - 14. Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications.
Part I Fundamental Concepts of Memristors and Neuromorphic Systems. - Prolog ? Memristor Minds. - 1. Are Memristors the Future of AI? ? A Review of Recent Progress and Future Perspectives. - 2. Biologically-Inspired Electronics with Memory Circuit Elements. - 3. Persuading Computers to Act More Like Brains. - 4. Memristors for More Than Just Memory: How to Use Learning to Expand Applications. - Part II Computational Models of Memristors. - 5. Computational Intelligence and Neuromorphic Computing Architectures. - 6. Reconfigurable Memristor Fabrics for Heterogeneous Computing. - 7. Statistical Memristor Model and Its Applications in Neuromorphic Computing. - 8. Adaptive Resonance Theory Design in Mixed Memristive-Fuzzy Hardware. - 9. Memristor SPICE Modeling. - Part III. Hardware Embodiments with Memristive Properties and Applications. - 10. Energy-Efficient Memristive Analog and Digital Electronics. - 11. Memristor Models for Pattern Recognition Systems. - 12. Phase Change Memory and Chalcogenide Materials Neuromorphic Applications: Emphasis on Synaptic Plasticity. - 13. A Columnar V1/V2 Visual Cortex Model and Emulation. - 14. Polymer and Nanoparticle-Composite Bistable Devices: Physics of Operation and Initial Applications.
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