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Advancing VLSI through Machine Learning
Advancing VLSI through Machine Learning
Innovations and Research Perspectives
This book explores the synergy between VLSI and Machine Learning and its applications across various domains. It will investigate how Machine Learning techniques can enhance the design and testing of VLSI circuits, improve power efficiency, optimize layouts, and enable novel architectures.
März 2025, ca. 254 Seiten, Materials, Devices, and Circuits, Englisch
Taylor and Francis
978-1-032-77428-2
This book explores the synergy between VLSI and Machine Learning and its applications across various domains. It will investigate how Machine Learning techniques can enhance the design and testing of VLSI circuits, improve power efficiency, optimize layouts, and enable novel architectures.
März 2025, ca. 254 Seiten, Materials, Devices, and Circuits, Englisch
Taylor and Francis
978-1-032-77428-2
Weitere Titel der Reihe: Materials, Devices, and Circuits
Alle anzeigenApplied Artificial Intelligence and Machine Learning Techniques for Engineering ...
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Human-Machine Interface Technology Advancements and Applications
Taylor and Francis, 2025
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Quantum-Dot Cellular Automata Circuits for Nanocomputing Applications
Taylor and Francis, 2025
978-1-032-42195-7
ca. 86.00 CHF
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Tunneling Field Effect Transistors
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978-1-032-35469-9
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Device Circuit Co-Design Issues in FETs
Taylor and Francis, 2025
978-1-032-41682-3
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Microwave Devices and Circuits for Advanced Wireless Communication
Design and Analysis
Taylor and Francis, 2024
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5G and Beyond Wireless Networks
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Negative Capacitance Field Effect Transistors
Physics, Design, Modeling and Applications
Taylor and Francis, 2023
978-1-03-244531-1
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Human-Machine Interface Technology Advancements and Applications
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Device Circuit Co-Design Issues in FETs
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978-1-03-241425-6
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