activity
20162023
most citedImplementation of Multilayer Perceptron Network with Highly Uniform Passive Memristive Crossbar Circuits

18 citations · 29 across the 6 of their papers we have counts for

collaborators

6 papers

cs.ET2023★ 2 cited

Thermal Crosstalk Analysis in RRAM Passive Crossbar Arrays

Shubham Pande, Bhaswar Chakrabarti, Anjan Chakravorty

As the packing density of resistive random access memory (RRAM) devices increases, the effect of thermal cross-talk across the devices in a crossbar array arrangement influences th…

cs.ET2022★ 1 cited

A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks

Wilfried Haensch, Anand Raghunathan, Kaushik Roy +4

Deep Learning neural networks are pervasive, but traditional computer architectures are reaching the limits of being able to efficiently execute them for the large workloads of tod…

cs.NE2021

2D-Motion Detection using SNNs with Graphene-Insulator-Graphene Memristive Synapses

Shubham Pande, Karthi Srinivasan, Suresh Balanethiram +2

The event-driven nature of spiking neural networks makes them biologically plausible and more energy-efficient than artificial neural networks. In this work, we demonstrate motion…

physics.app-ph2021

Quasi-HfO/ AlO and AlO/ HfO Based Memristor Devices: Role of Bi-layered Oxides in Digital Set and Analog Reset Switching

Pradip Basnet, Erik Anderson, Bhaswar Chakrabarti +3

Understanding the resistive switching behavior, or the resistance change, of oxide-based memristor devices, is critical to predicting their responses with known electrical inputs.…

cs.ET2017★ 18 cited

Implementation of Multilayer Perceptron Network with Highly Uniform Passive Memristive Crossbar Circuits

F. Merrikh Bayat, M. Prezioso, B. Chakrabarti +2

The progress in the field of neural computation hinges on the use of hardware more efficient than the conventional microprocessors. Recent works have shown that mixed-signal integr…

cs.ET2016★ 8 cited

Advancing Memristive Analog Neuromorphic Networks: Increasing Complexity, and Coping with Imperfect Hardware Components

F. Merrikh Bayat, M. Prezioso, B. Chakrabarti +2

We experimentally demonstrate classification of 4x4 binary images into 4 classes, using a 3-layer mixed-signal neuromorphic network ("MLP perceptron"), based on two passive 20x20 m…