Embedded Deep Learning: Algorithms, Architectures and Circuits for Always-On Neural Network Processing 2019 Edition Contributor(s): Moons, Bert (Author), Bankman, Daniel (Author), Verhelst, Marian (Author) |
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ISBN: 3319992228 ISBN-13: 9783319992228 Publisher: Springer OUR PRICE: $132.99 Product Type: Hardcover Published: November 2018 |
Additional Information |
BISAC Categories: - Technology & Engineering | Electronics - Circuits - General - Technology & Engineering | Signals & Signal Processing |
Dewey: 621.381 |
Physical Information: 0.56" H x 6.14" W x 9.21" (1.08 lbs) 206 pages |
Descriptions, Reviews, Etc. |
Publisher Description: This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning.
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