1 citations · 1 across the 6 of their papers we have counts for
6 papers
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.…
Regularization-based Framework for Quantization-, Fault- and Variability-Aware Training
Anmol Biswas, Raghav Singhal, Sivakumar Elangovan +2
Efficient inference is critical for deploying deep learning models on edge AI devices. Low-bit quantization (e.g., 3- and 4-bit) with fixed-point arithmetic improves efficiency, wh…
Temporal and Spatial Reservoir Ensembling Techniques for Liquid State Machines
Anmol Biswas, Sharvari Ashok Medhe, Raghav Singhal +1
Reservoir computing (RC), is a class of computational methods such as Echo State Networks (ESN) and Liquid State Machines (LSM) describe a generic method to perform pattern recogni…
Heracles: A HfO2 Ferroelectric Capacitor Compact Model for Efficient Circuit Simulations
Luca Fehlings, Md Hanif Ali, Paolo Gibertini +4
The growing use of ferroelectric-based technology, extending beyond conventional memory storage applications, necessitates the development of compact models that can be easily inte…
System-level Impact of Non-Ideal Program-Time of Charge Trap Flash (CTF) on Deep Neural Network
S. Shrivastava, A. Biswas, S. Chakrabarty +3
Learning of deep neural networks (DNN) using Resistive Processing Unit (RPU) architecture is energy-efficient as it utilizes dedicated neuromorphic hardware and stochastic computat…
Design Space and Variability Analysis of SOI MOSFET for Ultra-Low Power Band-to-Band Tunneling Neurons
Jay Sonawane, Shubham Patil, Abhishek Kadam +4
Large spiking neural networks (SNNs) require ultra-low power and low variability hardware for neuromorphic computing applications. Recently, a band-to-band tunneling-based (BTBT) i…