Hyperdimensional Computing For Next-Gen Edge
Language: English
Published by RASHID PUBLICATIONS, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 21.61
Quantity: 2 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input.The proposed frameworks utilize HDC's simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging computing paradigm. Furthermore, experiments highlight the modular nature of HDC's class hypervector construction, enabling iterative learning, sample unlearning, analysis of sensor contributions, and sensor influence removal.Custom benchmarking applications were created for Android deployment to further evaluate inference latency, memory usage, and energy consumption. The results further support HDC's efficiency claims, especially when compared to conventional machine learning, demonstrating comparable classification performance while remaining suitable for real-time, edge device deployment.Overall, this work establishes HDC as an adaptable and efficient machine learning technique through practical deployment to real-world smart devices, which has yet to be demonstrated in prior works. …
Seller Inventory # 9783024086113
- Title
- Hyperdimensional Computing For Next-Gen Edge
- Author
- Mohd Rashid
- Publisher
- RASHID PUBLICATIONS
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3024086110
- ISBN 13
- 9783024086113
- Item weight
- 148 grams
- Dimensions
- 229x152x5 mm
This book presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input.
The proposed frameworks utilize HDC's simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging computing paradigm. Furthermore, experiments highlight the modular nature of HDC's class hypervector construction, enabling iterative learning, sample unlearning, analysis of sensor contributions, and sensor influence removal.
Custom benchmarking applications were created for Android deployment to further evaluate inference latency, memory usage, and energy consumption. The results further support HDC's efficiency claims, especially when compared to conventional machine learning, demonstrating comparable classification performance while remaining suitable for real-time, edge device deployment.
Overall, this work establishes HDC as an adaptable and efficient machine learning technique through practical deployment to real-world smart devices, which has yet to be demonstrated in prior works.
"Synopsis" may belong to another edition of this title.
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