scholarly journals VO2 Carbon Nanotube Composite Memristor-Based Cellular Neural Network Pattern Formation

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1198
Author(s):  
Yiran Shen ◽  
Guangyi Wang
Keyword(s):  
Neural Network ◽  
Carbon Nanotube ◽  
Complex Space ◽  
Initial Conditions ◽  
Processing System ◽  
Cellular Neural Network ◽  
Edge Of Chaos ◽  
Time Patterns ◽  
Carbon Nanotube Composite ◽  
Network Pattern

A cellular neural network (CNN) based on a VO2 carbon nanotube memristor is proposed in this paper. The device is modeled by SPICE at first, and then the cell dynamic characteristics based on the device are analyzed. It is pointed out that only when the cell is at the sharp edge of chaos can the cell be successfully awakened after the CNN is formed. In this paper, we give the example of a 5 × 5 CNN, set specific initial conditions and observe the formed pattern. Because the generated patterns are affected by the initial conditions, the cell power supply can be pre-programmed to obtain specific patterns, which can be applied to the future information processing system based on complex space–time patterns, especially in the field of computer vision.

ON THE GENERATION OF SCROLL WAVES IN A THREE-DIMENSIONAL DISCRETE ACTIVE MEDIUM

1995 ◽  
Vol 05 (01) ◽  
pp. 313-320 ◽  
Author(s):  
LADISLAV PIVKA ◽  
ALEXANDER L. ZHELEZNYAK ◽  
CHAI WAH WU ◽  
LEON O. CHUA
Keyword(s):  
Neural Network ◽  
Active Medium ◽  
Initial Conditions ◽  
Three Dimensional ◽  
Cellular Neural Network ◽  
Inhomogeneous Media ◽  
Wave Patterns ◽  
Scroll Wave ◽  
Scroll Waves

This paper reports on the simulation, in three-dimensional cellular-neural-network (CNN) arrays of Chua’s circuits, of basic three-dimensional scroll wave patterns observed previously from other media. Among the simulated patterns are the straight scroll wave, twisted scroll wave in both homogeneous and inhomogeneous media, as well as the scroll ring. These types of waves have been obtained for only one set of circuit parameters by varying the initial conditions.

Optimizing Time-multiplexing Raster Cellular Neural Network simulator using genetic algorithms with RK8(6)

2011 ◽  
Vol 3 (6) ◽  
pp. 87-90
Author(s):  
O. H. Abdelwahed O. H. Abdelwahed ◽  
◽  
M. El-Sayed Wahed ◽  
O. Mohamed Eldaken
Keyword(s):  
Neural Network ◽  
Genetic Algorithms ◽  
Cellular Neural Network ◽  
Network Simulator

scholarly journals Supramolecular ionic polymer/carbon nanotube composite hydrogels with enhanced electromechanical performance

2020 ◽  
Vol 9 (1) ◽  
pp. 478-488 ◽  
Author(s):  
Yun-Fei Zhang ◽  
Fei-Peng Du ◽  
Ling Chen ◽  
Ka-Wai Yeung ◽  
Yuqing Dong ◽  
...  
Keyword(s):  
Carbon Nanotube ◽  
Ion Mobility ◽  
Artificial Muscles ◽  
Ionic Polymer ◽  
Composite Hydrogels ◽  
The Matrix ◽  
Electromechanical Performance ◽  
Carbon Nanotube Composite ◽  
Robotic Devices

AbstractElectroactive hydrogels have received increasing attention due to the possibility of being used in biomimetics, such as for soft robotics and artificial muscles. However, the applications are hindered by the poor mechanical properties and slow response time. To address these issues, in this study, supramolecular ionic polymer–carbon nanotube (SIPC) composite hydrogels were fabricated via in situ free radical polymerization. The polymer matrix consisted of carbon nanotubes (CNTs), styrene sulfonic sodium (SSNa), β-cyclodextrin (β-CD)-grafted acrylamide, and ferrocene (Fc)-grafted acrylamide, with the incorporation of SSNa serving as the ionic source. On applying an external voltage, the ions accumulate on one side of the matrix, leading to localized swelling and bending of the structure. Therefore, a controllable and reversible actuation can be achieved by changing the applied voltage. The tensile strength of the SIPC was improved by over 300%, from 12 to 49 kPa, due to the reinforcement effect of the CNTs and the supramolecular host–guest interactions between the β-CD and Fc moieties. The inclusion of CNTs not only improved the tensile properties but also enhanced the ion mobility, which lead to a faster electromechanical response. The presented electro-responsive composite hydrogel shows a high potential for the development of robotic devices and soft smart components for sensing and actuating applications.

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