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Neuromorphic Circuits for Nanoscale Devices

Hardback
November 2019
9788770220606
More details
  • Publisher
    River Publishers
  • Published
    6th November
  • ISBN 9788770220606
  • Language English
  • Pages 300 pp.
  • Size 6" x 9"
$110.00
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November 2019
9788770220590
More details
  • Publisher
    River Publishers
  • ISBN 9788770220590
  • Language English
  • Pages 300 pp.
  • Size 6" x 9"
$82.50

Nanoscale devices attracted significant research effort from the industry and academia due to their operation principals being based on different physical properties which provide advantages in the design of certain classes of circuits over conventional CMOS transistors.

Neuromorphic Circuits for Nanoscale Devices contains recent research papers presented in various international conferences and journals to provide insight into how the operational principles of the nanoscale devices can be utilized for the design of neuromorphic circuits for various applications of non-volatile memory, neural network training/learning, and image processing.

The topics discussed in the book include:

  • Nanoscale Crossbar Memory Design
  • Q-Learning and Value Iteration using Nanoscale Devices
  • Image Processing and Computer Vision Applications for Nanoscale Devices
  • Nanoscale Devices-based Cellular Nonlinear/Neural Networks

Introduction
1. Crossbar Memory Simulation and Performance Evaluation
2. Memristor Digital Memory
3. Multi-Level Memory Architecture
4. Neuromorphic Building Blocks with Memristors
5. Value Iteration with Memristors
6. 2-D Array of Multi-Peak Resonant Tunneling Diodes Based Color Image Processing
7. Color Image Processing with Multi-Peak Resonant Tunneling Diodes
8. Design of a Velocity-Tuned Filter Using a Matrix of Resonant Tunneling Diodes
9. Image Processing by a Programmable Artificial Retina Comprising Quantum Dots and Memristors
10. Memristor-based Cellular Nonlinear/Neural Network: Design, Analysis and Applications
11. Dynamic analysis of memristor-based neural network and its application
Appendix
References

Pinaki Mazumder

Pinaki Mazumder is at University of Michigan, Ann Arbor.

Yalcin Yilmaz

Yilcin Yilmaz is at University of Michigan, Ann Arbor.

Idongesit Ebong

Idongesit Ebong is at University of Michigan, Ann Arbor.  

Woo Hyung Lee

Woo Hyung Lee is at University of Michigan, Ann Arbor.  

Memristor
Crossbar Memory
Q-Learning
Resonant Tunnelling Diode (RTD)
Cellular Neural/Nonlinear Network (CNN)
Computer Vision