Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices

1. Hardware Spiking Artificial Neurons, Their Response Function, and Noises
Doo Seok Jeong

2. Synaptic Plasticity with Memristive Nanodevices
Selina Barbera, Fabien Alibart

3. Neuromemristive Systems: A Circuit Design Perspective
Cory Merkel, Dhireesha Kudithipudi

4. Memristor-Based Platforms: A Comparison Between Continous-Time and Discrete-Time Cellular Neural Networks
Young-Su Kim, Sang-Hak Shin, Jacopo Secco, Keyong-Sik Min, Fernando Corinto

5. Reinterpretation of Magnetic Tunnel Junctions as Stochastic Memristive Devices
Adrien F. Vincent, Nicolas Locatelli, Damien Querlioz

6. Multiple Binary OxRAMs as Synapses for Convolutional Neural Networks
E. Vianello, D. Garbin, O. Bichler, G. Piccolboni, G. Molas, B. Salvo, L. Perniola

7. Nonvolatile Memory Crossbar Arrays for Non-von Neumann Computing
Severin Sidler, Jun-Woo Jang, Geoffrey W. Burr, Robert M. Shelby, Irem Boybat, Carmelo Nolfo, Pritish Narayanan, Kumar Virwani, Hyunsang Hwang

8. Novel Biomimetic Si Devices for Neuromorphic Computing Architecture
U. Ganguly, Bipin Rajendran

9. Exploiting Variability in Resistive Memory Devices for Cognitive Systems
Vivek Parmar, Manan Suri

10. TheoreticalAnalysisofSpike-Timing-Dependent Plasticity Learning with Memristive Devices
Damien Querlioz, Olivier Bichler, Adrien F. Vincent, Christian Gamrat

Nyckelord: Engineering, Circuits and Systems, User Interfaces and Human Computer Interaction, Computational Intelligence, Nanotechnology and Microengineering