Titlebook: Innovations in VLSI, Signal Processing and Computational Technologies; Select Proceedings o Gayatri Mehta,Nilmini Wickramasinghe,Deepti Kak

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书目名称Innovations in VLSI, Signal Processing and Computational Technologies影响因子(影响力)学科排名




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书目名称Innovations in VLSI, Signal Processing and Computational Technologies网络公开度学科排名




书目名称Innovations in VLSI, Signal Processing and Computational Technologies被引频次




书目名称Innovations in VLSI, Signal Processing and Computational Technologies被引频次学科排名




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书目名称Innovations in VLSI, Signal Processing and Computational Technologies年度引用学科排名




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书目名称Innovations in VLSI, Signal Processing and Computational Technologies读者反馈学科排名

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SOT-MRAM Memories for Energy Efficient Embedded and AI Applications, computing architectures. With this comes the major challenge of holistic efficiency particularly low power and high-performance implementations in the light of memory system architectures. In this context, modern spintronics based non-volatile memory technologies (NVM) such as spin–orbit torque has

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A Comprehensive Review to Investigate the Effect of Read Port Topology on the Performance of Differe has driven designers to report SRAM bit cells with varying topologies. The 7T cell is one of the most popular bit cell topologies. As a consequence, five different 7T cells with a common internal memory core configuration and different read port topologies are reviewed in this paper. The technolog

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,A Comparative Performance Analysis of 10 T and 11 T SRAM Cells,crucial among the type of memories since it is the one working closely in synchronization with the central processing unit. There are millions of SRAM cells inside cache memory. SRAM cells must therefore possess a few essential attributes for cache memory to be reliable, including low dynamic and st

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All-,Type Digital Circuits Using Single Gate and Double Gate Organic Field Effect Transistors,r modulation makes double gate (DG) organic transistor a better choice for electronic equipments due to the presence of two conducting channels. A significant enhancement of 46%, 67%, and 40% is obtained in transconductance, ON current, and mobility, respectively. Further, this paper compares two co

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,Self-attention-Based Deep Learning Approach for Machine Translation of Low Resource Languages: A Cacompatibility have made machine translation (MT) a difficult process that is full of difficulties, especially in comparison to a physical conversion. The development of neural-based methods has brought machine translation outcomes closer to what people would expect. The seq-to-seq strategy, which us

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Reinforcement Learning Method for Identifying Health Issues for People with Chronic Diseases,. For these reasons, it is thought that clinically examining medical records using traditional and machine learning technologies could be a beneficial, real, and most crucially cost-effective alternative to human medical professionals. Understanding the significance of early detection in preventing