S. Yamuna
Papers
1
Total Citations
7
H-Index
1
About
S. Yamuna is a researcher at the forefront of merging ancient computational principles with modern artificial intelligence. Her primary research areas include Vedic mathematics, neural network design, and digital logic optimization. Yamuna’s most notable contribution is the pioneering concept of realizing neuronal logic gates using Vedic mathematics, a breakthrough that reimagines the fundamental building blocks of logic circuits through the lens of ancient Indian mathematical sutras. This innovative approach, detailed in her highly cited 2015 paper (7 citations), demonstrates how artificial neural networks—traditionally used for pattern recognition, system identification, and robotics—can be enhanced by Vedic techniques to achieve more efficient parallel processing architectures. By bridging classical wisdom with cutting-edge AI, Yamuna’s work offers a novel pathway for optimizing neural network performance in complex applications, from control systems to predictive modeling. Her research stands as a testament to the untapped potential of interdisciplinary thinking, inspiring a new generation of engineers to explore how historical mathematical frameworks can solve contemporary computational challenges.
Research Focus
Key Achievements
Top Papers
- 1Neuronal Logic gates realization using Vedic mathematics7 citations · 2015