Results 101 to 110 of about 491 (232)

Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

Advanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

Second generation current conveyor based capacitorless floating memristor emulator

This article offers a novel flux controlled floating memristor emulator based on second-generation current conveyor (CCII). The floating memristor is designed using two CCIIs, one resistor, and one PMOS transistor.
Pandey, Neeta, Minaei, Shahram, Kumar, Manjeet, Kumar, Navnit   +3 more
core   +1 more source

Electroencephalogram‐Driven Recognition of Parkinson's Disease Through a Mycelium‐Inspired Memristive Reservoir Computing Circuit

Advanced Intelligent Systems, EarlyView.
This work presents a bio‐inspired computing framework for Parkinson's disease analog recognition using electroencephalogram signals. Temporally encoded EEG features stimulate a mycelium‐inspired memristive reservoir, where disease‐related patterns emerge through physical spatiotemporal dynamics.
Ioannis K. Chatzipaschalis, Ioannis Tompris, Pantelis Fraidakis, Iosif‐Angelos Fyrigos, Antonio Rubio, Georgios Ch. Sirakoulis   +5 more
wiley   +1 more source

Experimental demonstration of associative memory with memristive neural networks

, 2009
When someone mentions the name of a known person we immediately recall her face and possibly many other traits. This is because we possess the so-called associative memory - the ability to correlate different memories to the same fact or event ...
Massimiliano Di Ventra, Yuriy Pershin
core  

Compact grounded memristor model with resistorless and tunability features

Frontiers in Electronics
This research article provides a circuit illustration of a grounded memristor emulator. An operational transconductance amplifier (OTA) is one of its active components, along with two transistors and one capacitor.
Ankit Mehta, Arash Ahmadi, Majid Ahmadi
doaj   +1 more source

Stable Neural Signal Recording Processed by Memristor‐Based Reservoir Computing System

Advanced Intelligent Systems, EarlyView.
This work introduces a memristor‐based reservoir computing (RC) system for real‐time, energy‐efficient processing of neural signals in brain‐machine interface (BMI). Combined with flexible mesh neural probes with tissue‐like flexibility and subcellular‐scale features that enable consistent, long‐term tracking of single‐cell neural activities, the ...
Soohyeon Kim, Yuting Wu, Finn Moore, Mingtao Hu, Xiaoyu Zhang, Sangmin Yoo, Eric Yeu‐Jer Lee, Hao Shen, Yichun He, Jia Liu, Wei D. Lu   +10 more
wiley   +1 more source

A Neuromorphic Simulation Framework for Indium‐Gallium‐Zinc‐Oxide Charge‐Trap Synaptic Transistors: From Device Modeling to System Simulation

Advanced Intelligent Systems, EarlyView.
This work presents a comprehensive framework bridging device fabrication, modeling, and system‐level simulation for an indium‐gallium‐zinc‐oxide (IGZO) charge‐trap synaptic transistor‐based neuromorphic system. By developing a precise SPICE model derived from fabricated IGZO synaptic transistors, the study incorporates parasitic RC loads into array ...
Yumin Yun, Junhyeong Park, Sunyeol Bae, Chae‐Hwan Park, Dong Hyeon Lee, Soo‐Yeon Lee   +5 more
wiley   +1 more source

Neuromorphic Denoising with Fully Analog Memristive In‐Memory Computing

Advanced Intelligent Systems, EarlyView.
This article borrows the concepts of episodic memory in human brains to experimentally implement a memristor‐based neuromorphic denoising process. A homogeneous memristor processing unit is experimentally demonstrated for both temporal storage and neural network computation, imitating the synapses in the human brain.
Daijing Shi, Teng Zhang, Yuqi Li, Yaoyu Tao, Bonan Yan, Yuchao Yang   +5 more
wiley   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source