[HTML][HTML] Dynamical analysis and synchronization control of flux-controlled memristive chaotic circuits and its FPGA-Based implementation
J Luo, W Tang, Y Chen, X Chen, H Zhou - Results in Physics, 2023 - Elsevier
This paper focuses on addressing the synchronization control problem of memristive chaos
through the investigation of a single feedback controller strategy. Our objective is to deploy …
through the investigation of a single feedback controller strategy. Our objective is to deploy …
ReRAM-based in-memory computing for search engine and neural network applications
Y Halawani, B Mohammad, MA Lebdeh… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Resource-constrained computing devices such as those used in IoTs require low-power,
high performance, and small size to be enabled to operate efficiently. Resistive random …
high performance, and small size to be enabled to operate efficiently. Resistive random …
High-speed memristive ternary content addressable memory
KP Gnawali, S Tragoudas - IEEE Transactions on Emerging …, 2021 - ieeexplore.ieee.org
This article presents an ultra-high-speed memristor-based non-volatile Ternary Content
Addressable Memory (TCAM) for use in real-time and big-data applications that require low …
Addressable Memory (TCAM) for use in real-time and big-data applications that require low …
Memristor based circuit design for liquid state machine verified with temporal classification
A Henderson, C Yakopcic, S Harbour… - … Joint Conference on …, 2022 - ieeexplore.ieee.org
Spiking neural networks represent a transition from deep networks and tensor engines to
more dynamic systems better suited for carrying out decisions based on temporal patterns …
more dynamic systems better suited for carrying out decisions based on temporal patterns …
Beyond cmos
S Das, A Chen, M Marinella - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Dimensional and functional scaling 1 1 Functional Scaling: Suppose that a system has been
realized to execute a specific function in a given, currently available, technology. We say that …
realized to execute a specific function in a given, currently available, technology. We say that …
Circuit Implementation, Synchronization of Multistability, and Image Encryption of a Four‐Wing Memristive Chaotic System
G Peng, F Min, E Wang - Journal of Electrical and Computer …, 2018 - Wiley Online Library
The four‐wing memristive chaotic system used in synchronization is applied to secure
communication which can increase the difficulty of deciphering effectively and enhance the …
communication which can increase the difficulty of deciphering effectively and enhance the …
Stateful memristor-based search architecture
Y Halawani, MA Lebdeh, B Mohammad… - … Transactions on Very …, 2018 - ieeexplore.ieee.org
Computer vision and recognition is emerging as one of the important pillars in artificial
intelligence systems. It is a vital way to interpret the collected data and find matching …
intelligence systems. It is a vital way to interpret the collected data and find matching …
Efficient memristor-based architecture for intrusion detection and high-speed packet classification
V Bontupalli, C Yakopcic, R Hasan… - ACM Journal on Emerging …, 2018 - dl.acm.org
Deep packet inspection (DPI) is a critical component to prevent intrusion detection. This
requires a detailed analysis of each network packet header and body. Although this is often …
requires a detailed analysis of each network packet header and body. Although this is often …
Memristor Based Liquid State Machine with Method for In-Situ Training
A Henderson, C Yakopcic, C Merkel… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Spiking neural network (SNN) hardware has gained significant interest due to its ability to
process complex data in size, weight, and power (SWaP) constrained environments …
process complex data in size, weight, and power (SWaP) constrained environments …
A Memristor-Based Liquid State Machine for Auditory Signal Recognition
SA Henderson Jr - 2021 - rave.ohiolink.edu
Abstract Spiking Neural Networks (SNNs) are the third generation of neural networks that
incorporate the notion of time in their model. SNNs are starting to be deployed in …
incorporate the notion of time in their model. SNNs are starting to be deployed in …