Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1Intelligence in Biological Systems
- 2Principles of Artificial Neural Networks
- 3Artificial Synapses
- 4Artificial Neurons
- 5Examples of Applications in Artificial Neural Networks
- 6System Design
- 7Neuromorphic Algorithms
- 8Lifelong Learning with AI Algorithms and Hardware
- 9Practice Problems
- Index
- References
5 - Examples of Applications in Artificial Neural Networks
Published online by Cambridge University Press: 01 January 2026
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1Intelligence in Biological Systems
- 2Principles of Artificial Neural Networks
- 3Artificial Synapses
- 4Artificial Neurons
- 5Examples of Applications in Artificial Neural Networks
- 6System Design
- 7Neuromorphic Algorithms
- 8Lifelong Learning with AI Algorithms and Hardware
- 9Practice Problems
- Index
- References
Summary
The chapter focuses on the network and architecture layers of the design stack building up from device and circuit concepts introduced in Chapters 3 and 4. Architectural advantages like address-event representation stemming from neuromorphic models by leveraging spiking sparsity are discussed. Near-memory and in-memory architectures using CMOS implementations are first discussed followed by several emerging technologies, namely, correlated electron semiconductor-based devices, filamentary devices, organic devices, spintronic devices, and photonic neural networks.
Keywords
Information
- Type
- Chapter
- Information
- Introduction to Neuromorphic Computing , pp. 113 - 134Publisher: Cambridge University PressPrint publication year: 2026
References
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