1 citations · 1 across the 5 of their papers we have counts for
6 papers
A Solution-Processed Ti/Pt/NiOx/Ag RRAM Device with Multiple Forming-Free Non-Volatile Intermediate States
Abhrajit Roy, Chopali Chanchal Sahu, Rudraksh Sangore +5
Artificial neural networks (ANN) implemented on crossbar arrays of non-volatile synaptic devices are known to consume much less energy compared to that implemented on conventional…
Warm-Start Quantum Approximate Optimization Algorithm for QAM MIMO Data Detection
Soumyadip Paul, Sourav Banerjee, Debanjan Bhowmik +1
Data detection in large-scale multiple-input multiple-output (MIMO) systems with higher-order quadrature amplitude modulation (QAM) remains a challenging problem due to the exponen…
Artificial Neural Network (ANN) -- Oscillatory Neural Network (ONN) Hybrid System Using Domain-Wall Synapse Devices and Nano-Constriction Spin Hall Nano Oscillators
Raman Hissariya, Gajjala Venkata Sreekar Reddy, Ashwin Tulapurkar +1
A coupled spintronic oscillator array has been considered attractive for neuromorphic computing applications. Experimental reports have shown the nano-constriction geometry to be a…
Symbol Detection in a MIMO Wireless Communication System Using a FeFET-coupled CMOS Ring Oscillator Array
Harsh Kumar Jadia, Abhinaba Ghosh, Md Hanif Ali +11
Symbol decoding in multiple-input multiple-output (MIMO) wireless communication systems requires the deployment of fast, energy-efficient computing hardware deployable at the edge.…
Vertically Integrated Dual-memtransistor Enabled Reconfigurable Heterosynaptic Sensorimotor Networks and In-memory Neuromorphic Computing
Srilagna Sahoo, Abin Varghese, Aniket Sadashiva +4
Neuromorphic in-memory computing requires area-efficient architecture for seamless and low latency parallel processing of large volumes of data. Here, we report a compact, vertical…
Phase-Binarized Spintronic Oscillators for Combinatorial Optimization, and Comparison with Alternative Classical and Quantum Methods
Neha Garg, Sanyam Singhal, Nakul Aggarwal +3
Solving combinatorial optimization problems efficiently through emerging hardware by converting the problem to its equivalent Ising model and obtaining its ground state is known as…