Advances in neuromorphic hardware exploiting emerging nanoscale devices

• Other Authors: Suri, Manan
• Format: Electronic eBook
• Language: English
• Published: New Delhi : Springer, 2017.
• Series: Cognitive systems monographs ; v. 31.
• Subjects: Neural networks (Computer science); Computer architecture.; Analog CMOS integrated circuits.; elektronické knihy; electronic books
• ISBN: 9788132237037; 9788132237013
• Physical Description: 1 online resource (216 pages)

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)...

Table of Contents:

• Preface; Contents; Dr. Manan Suri; Hardware Spiking Artificial Neurons, Their Response Function, and Noises; 1 Introduction; 1.1 Biological Neurons; 1.2 Neuronal Response Function; 1.3 Neuronal Noises; 1.4 Artificial Neuron Models; 2 Hardware Spiking Neurons; 2.1 Silicon Neurons; 2.2 Emerging Spiking Neurons; 3 Summary and Outlook; References; Synaptic Plasticity with Memristive Nanodevices; 1 Introduction; 2 Neuromorphic Systems: Basic Processing and Data Representation; 2.1 Data Encoding in Neuromorphic Systems; 2.2 Spike Computing for Neuromorphic Systems.
• 3 Synaptic Plasticity for Information Computing3.1 Causal Approach: Synaptic Learning Versus Synaptic Adaptation; 3.2 Phenomenological Approach: Short-Term Plasticity Versus Long-Term Plasticity; 4 Synaptic Plasticity Implementation in Neuromorphic Nanodevices; 4.1 Causal Implementation of Synaptic Plasticity; 4.2 Phenomenological Implementation of Synaptic Plasticity; 5 Conclusions; References; Neuromemristive Systems: A Circuit Design Perspective; 1 Introduction: Taking a Cue from Nature; 2 Memristor Overview; 3 Voltage Versus Current-Mode Circuit Designs for NMSs.
• 4 Neuron Circuits: Primary Information Processing Units4.1 Input Stage; 4.2 Activation Function; 5 Synapse Circuits: Communication and Memory; 6 Plasticity Circuits: Adaptation/Learning; 7 Summary and Outlook; References; Memristor-Based Platforms: A Comparison Between Continous-Time and Discrete-Time Cellular Neural Networks; 1 Introduction; 2 Backgorund; 3 New Memristance Restoring Circuit; 4 Simulation Results; 5 Cellular Automata and DTCNNs; 6 Belief Propagation Inspired Algorithm and Cellular Automaton Equivalence for RGB Image Processing; 7 Element Detection in RGB Image; 8 Conclusions.
• Multiple Binary OxRAMs as Synapses for Convolutional Neural Networks1 Multiple Binary OxRAM Devices as Artificial Synapses; 2 Convolutional Neural Network Architecture; 3 Synaptic Weight Resolution and Tolerance to Variability; 4 Conclusions; References; Nonvolatile Memory Crossbar Arrays for Non-von Neumann Computing; 1 Introduction; 2 Considerations for a Crossbar Implementation; 3 Phase-Change Memory (PCM): Results; 3.1 Experimental Results; 4 Non-filamentary RRAM Results; 4.1 Fabrication of PCMO Devices; 4.2 Simulation Results; 5 Discussion; 6 Conclusions; References.