Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Intelligence in Biological Systems
- 2 Principles of Artificial Neural Networks
- 3 Artificial Synapses
- 4 Artificial Neurons
- 5 Examples of Applications in Artificial Neural Networks
- 6 System Design
- 7 Neuromorphic Algorithms
- 8 Lifelong Learning with AI Algorithms and Hardware
- 9 Practice Problems
- Index
- References
9 - Practice Problems
Published online by Cambridge University Press: 01 January 2026
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Intelligence in Biological Systems
- 2 Principles of Artificial Neural Networks
- 3 Artificial Synapses
- 4 Artificial Neurons
- 5 Examples of Applications in Artificial Neural Networks
- 6 System Design
- 7 Neuromorphic Algorithms
- 8 Lifelong Learning with AI Algorithms and Hardware
- 9 Practice Problems
- Index
- References
Summary
This chapter provides a selection of problems relevant to the field of neuromorphic computing that intersects materials science, electrical engineering, computer science, neural networks, and device design for realizing AI in hardware and algorithms. The emphasis on interdisciplinary nature of neuromorphic computing is apparent.
Keywords
Information
- Type
- Chapter
- Information
- Introduction to Neuromorphic Computing , pp. 182 - 188Publisher: Cambridge University PressPrint publication year: 2026
References
Zhou, Y. and Ramanathan, S., 2012. Relaxation dynamics of ionic liquid – VO2 interfaces and influence in electric double-layer transistors. Journal of Applied Physics, 111(8), pp. 084508-1–084508-7.10.1063/1.4704689CrossRefGoogle Scholar
Nowotny, M. K., Bak, T. and Nowotny, J., 2006. Electrical properties and defect chemistry of TiO2 single crystal. I. Electrical conductivity. The Journal of Physical Chemistry B, 110(33), pp. 16270–16282.Google ScholarPubMed
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