Evolution of a two-dimensional quantum cellular neural network driven by an external field

1999 ◽  
Vol 85 (5) ◽  
pp. 2952-2961 ◽  
Author(s):  
Bi Qiao ◽  
Harry E. Ruda
Keyword(s):  
Neural Network ◽  
External Field ◽  
Cellular Neural Network ◽  
Two Dimensional

THE MOSAIC PATTERNS OF CNN WITH SYMMETRIC FEEDBACK TEMPLATE

2008 ◽  
Vol 18 (02) ◽  
pp. 375-390 ◽  
Author(s):  
YUNQUAN KE
Keyword(s):  
Neural Network ◽  
Parameter Space ◽  
Sufficient Conditions ◽  
Cellular Neural Network ◽  
Necessary And Sufficient Conditions ◽  
Two Dimensional ◽  
Geometric Methods ◽  
Variable Substitution ◽  
Necessary And Sufficient

In this paper, the mosaic patterns of the two-dimensional cellular neural network (CNN) with symmetric feedback template are investigated. For our CNN system, the parameter space is constructed by the output synaptic weights and the threshold, and it is partitioned into finitely many regions through geometric methods and variable substitution. Fixing the output synaptic weights and the threshold in some regions, we give the necessary and sufficient conditions to all mosaic patterns of the CNN systems.

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 Heat induction in two-dimensional graphene–Fe3O4 nanohybrids for magnetic hyperthermia applications with artificial neural network modeling

RSC Advances ◽  
2021 ◽  
Vol 11 (35) ◽  
pp. 21702-21715
Author(s):  
M. S. Dar ◽  
Khush Bakhat Akram ◽  
Ayesha Sohail ◽  
Fatima Arif ◽  
Fatemeh Zabihi ◽  
...  
Keyword(s):  
Neural Network ◽  
Magnetic Field ◽  
Artificial Neural Network ◽  
Network Modeling ◽  
Magnetic Hyperthermia ◽  
Alternating Magnetic Field ◽  
Neural Network Modeling ◽  
Two Dimensional ◽  
Artificial Neural Network Modeling ◽  
Heat Induction

Synthesis of Fe3O4–graphene (FG) nanohybrids and magnetothermal measurements of FxG100–x (x = 0, 25, 45, 65, 75, 85, 100) nanohybrids (25 mg each) at a 633 kHz alternating magnetic field of strength 9.1 mT.

Deep convolutional neural networks for human movement detection using wireless signals

2021 ◽  
pp. 1-10
Author(s):  
Chien-Cheng Leea ◽  
Zhongjian Gao ◽  
Xiu-Chi Huanga
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Convolutional Neural Network ◽  
Detection System ◽  
Deep Convolutional Neural Network ◽  
Human Detection ◽  
Two Dimensional ◽  
Dimensional Matrix ◽  
State Classification ◽  
Propagation Paths

This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet’s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective.

Convolutional Neural Network Based Symbol Detector for Two-dimensional Magnetic Recording

2020 ◽  
pp. 1-1
Author(s):  
Jinlu Shen ◽  
Benjamin J. Belzer ◽  
Krishnamoorthy Sivakumar ◽  
Kheong Sann Chan ◽  
Ashish James
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Magnetic Recording ◽  
Two Dimensional ◽  
Two Dimensional Magnetic Recording
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