E-LIB Suche - Ergebnisse für: Prabhu, Nagaraj Lakshmana

1

Neuromorphic In-Memory RRAM NAND/NOR Circuit Performance An..:

Prabhu, Nagaraj Lakshmana ; Raghavan, Nagarajan
IEEE Access. 10 (2022) - p. 125112-125135 , 2022

Link: https://doi.org/10.1109/..

2

Computational Failure Analysis of In-Memory RRAM Architectu..:

Prabhu, Nagaraj Lakshmana ; Raghavan, Nagarajan
IEEE Access. 9 (2021) - p. 168093-168106 , 2021

Link: https://doi.org/10.1109/..

3

Generalized Convolution Simulation Stack for RRAM Device ba..:

, In: 2020 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA),

Prabhu, Nagaraj Lakshmana ; Raghavan, Nagarajan - p. 1-6 , 2020

Link: https://doi.org/10.1109/..

4

Exploring the Power – Prediction Accuracy Trade-Off in a De..:

, In: 2019 8th International Symposium on Next Generation Electronics (ISNE),

Prabhu, Nagaraj Lakshmana ; Jun, Desmond Loy Jia ; Dananjaya, Putu Andhita... - p. 1-3 , 2019

Link: https://doi.org/10.1109/..

5

Exploring the impact of variability in resistance distribut..:

Prabhu, Nagaraj Lakshmana ; Loy, Desmond Jia Jun ; Dananjaya, Putu Andhita...
A18A5b0056. , 2020

Link: https://hdl.handle.net/1..

6

Neuromorphic In-Memory RRAM NAND/NOR Circuit Performance An..:

Nagaraj Lakshmana Prabhu ; Nagarajan Raghavan
https://ieeexplore.ieee.org/document/9936672/. , 2022

Link: https://doi.org/10.1109/..

7

Computational Failure Analysis of In-Memory RRAM Architectu..:

Nagaraj Lakshmana Prabhu ; Nagarajan Raghavan
https://ieeexplore.ieee.org/document/9654206/. , 2021

Link: https://doi.org/10.1109/..

8

Exploring the Impact of Variability in Resistance Distribut..:

Nagaraj Lakshmana Prabhu ; Desmond Loy Jia Jun ; Putu Andhita Dananjaya...
https://www.mdpi.com/2079-9292/9/3/414. , 2020

Link: https://doi.org/10.3390/..

9

The Virtual Screening of Compounds from the ZINC Database a..:

Priyankha, Sridhar ; Polk, Shahrazad ; Thilagavathi, Ramasamy...
ChemistrySelect. 9 (2024) 10 - p. , 2024

Link: https://doi.org/10.1002/..

10

Molecular characterization suggests kinetic modulation of e..:

Nayak, B. Nagaraj ; Rajagopal, Kalaimagal ; Shunmugasundaram, Revathi...
VirusDisease. 34 (2023) 2 - p. 236-247 , 2023

Link: https://doi.org/10.1007/..

11

A Machine Learning Approach to Optimize, Model, and Predict..:

Kumar, S. Lakshmana ; Jacintha, V. ; Mahendran, A....
Hindawi Advances in Materials Science and Engineering Volume 2022, Article ID 4856089, 11 pages https://doi.org/10.1155/2022/4856089. , 2022

Link: https://ssrn.com/abstrac..

12

Sustainable hydrogen production for the greener environment..:

Rao, V.Navakoteswara ; Reddy, N.Lakshmana ; Kumari, M.Mamatha...
Journal of Environmental Management. 248 (2019) - p. 109246 , 2019

Link: https://doi.org/10.1016/..

13

A review on frontiers in plasmonic nano-photocatalysts for ..:

Reddy, N. Lakshmana ; Rao, V. Navakoteswara ; Vijayakumar, M....
International Journal of Hydrogen Energy. 44 (2019) 21 - p. 10453-10472 , 2019

Link: https://doi.org/10.1016/..

14

Coordinating electric vehicle charging with multiagent deep..:

Maguluri, Lakshmana Phaneendra ; Umasankar, A. ; Vijendra Babu, D....
Sustainable Computing: Informatics and Systems. 43 (2024) - p. 100993 , 2024

Link: https://doi.org/10.1016/..

15

A Machine Learning Approach to Optimize, Model, and Predict..:

Lakshmana Kumar, S. ; Jacintha, V. ; Mahendran, A....
Advances in Materials Science and Engineering. 2022 (2022) - p. 1-11 , 2022

Link: https://doi.org/10.1155/..