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Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices [electronic resource] / edited by Manan Suri.

Contributor(s): Suri, Manan [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Cognitive Systems Monographs: 31Publisher: New Delhi : Springer India : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XIII, 210 p. 123 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9788132237037.Subject(s): Electronic circuits | User interfaces (Computer systems) | Human-computer interaction | Computational intelligence | Microtechnology | Microelectromechanical systems | Electronic Circuits and Systems | User Interfaces and Human Computer Interaction | Computational Intelligence | Microsystems and MEMSAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.3815 Online resources: Click here to access online
Contents:
Phase Change Memory for Neuromorphics -- Filamentary resistive memory for Neuromorphics -- Metal oxide based memory for Neuromorphics -- Nano Organic Transistors for Neuromorphics -- Neuromorphic System design -- Neuromorphic System and algorithms optimization -- Memristor Technology for Neuromorphics -- PCMO based devices for Neuromorphics -- Resistive Memory for Neuromorphics -- Overall Perspective on Neuromorphic Hardware.
In: Springer Nature eBookSummary: This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.
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Phase Change Memory for Neuromorphics -- Filamentary resistive memory for Neuromorphics -- Metal oxide based memory for Neuromorphics -- Nano Organic Transistors for Neuromorphics -- Neuromorphic System design -- Neuromorphic System and algorithms optimization -- Memristor Technology for Neuromorphics -- PCMO based devices for Neuromorphics -- Resistive Memory for Neuromorphics -- Overall Perspective on Neuromorphic Hardware.

This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

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