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VLSI and hardware implementations using modern machine learning methods / edited by Sandeep Saini, Kusum Lata and G.R. Sinha.

Contributor(s): Material type: TextTextPublisher: Boca Raton, FL : CRC Press, 2022Edition: First editionDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781003201038
  • 1003201032
  • 9781000523812
  • 1000523810
  • 9781000523843
  • 1000523845
Subject(s): DDC classification:
  • 006.3/1 23/eng/20211014
LOC classification:
  • TK7874.75
Online resources:
Contents:
VLSI and hardware implementation using machine learning methods: a systematic literature review / Kusum Lata, Sandeep Saini, G R Sinha -- Machine learning for testing of VLSI circuit / Abhishek Choubey, Shruti Bhargava Choubey -- Online checkers to detect hardware trojans in AES hardware accelerators / Sree Ranjani Rajendran, Rajat Subhra Chakraborty.
Summary: "Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine learning based methods, algorithms, architectures, and frameworks designed for VLSI design. Focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. It contains chapters on case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design and hardware realization using machine learning techniques"-- Provided by publisher.
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VLSI and hardware implementation using machine learning methods: a systematic literature review / Kusum Lata, Sandeep Saini, G R Sinha -- Machine learning for testing of VLSI circuit / Abhishek Choubey, Shruti Bhargava Choubey -- Online checkers to detect hardware trojans in AES hardware accelerators / Sree Ranjani Rajendran, Rajat Subhra Chakraborty.

"Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine learning based methods, algorithms, architectures, and frameworks designed for VLSI design. Focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. It contains chapters on case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design and hardware realization using machine learning techniques"-- Provided by publisher.

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