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Anup Dandapat
Researcher at National Institute of Technology, Meghalaya
Publications - 65
Citations - 764
Anup Dandapat is an academic researcher from National Institute of Technology, Meghalaya. The author has contributed to research in topics: CMOS & Content-addressable memory. The author has an hindex of 11, co-authored 62 publications receiving 611 citations. Previous affiliations of Anup Dandapat include Jadavpur University & Indian Institute of Engineering Science and Technology, Shibpur.
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Journal ArticleDOI
Performance Analysis of a Low-Power High-Speed Hybrid 1-bit Full Adder Circuit
TL;DR: In this paper, a hybrid 1-bit full adder design employing both complementary metal-oxide-semiconductor (CMOS) logic and transmission gate logic is reported and is found to offer significant improvement in terms of power and speed.
Proceedings ArticleDOI
High speed ASIC design of complex multiplier using Vedic Mathematics
TL;DR: A high speed complex multiplier design using Vedic mathematics is presented in this paper, where partial products and sums are generated in one step which reduces the carry propagation from LSB to MSB.
Journal Article
A 1.2-ns16×16-Bit Binary Multiplier Using High Speed Compressors
TL;DR: A 16×16 bit multiplier has been developed using special kind of adders that are capable to add five/six/seven bits per decade and Binary counter property has been merged with the compressor property to develop high order compressors.
Journal ArticleDOI
ASIC design of a high speed low power circuit for factorial calculation using ancient Vedic mathematics
TL;DR: ASIC design of a high speed low power circuit for factorial calculation of a number and improvements in speed and power consumption were found in comparison with UT and NND based implementations, respectively.
Journal ArticleDOI
Self-Controlled High-Performance Precharge-Free Content-Addressable Memory
TL;DR: A self-controlled precharge-free CAM (SCPF-CAM) structure is proposed for high-speed applications and is useful in applications where search time is very crucial to design larger word lengths.