Classificationofscale-freenetworks Kwang-IlGoh*,EulsikOh*,HawoongJeong † ,ByungnamKahng* ‡ ,andDoochulKim* *SchoolofPhysicsandCenterforTheoreticalPhysics,SeoulNationalUniversity,Seoul151-747,Korea;and † DepartmentofPhysics,KoreaAdvancedInstitute ofScienceandTechnology,Daejon305-701,Korea EditedbyLeo...
Our experimental results conducted using several real data sets demonstrate the superiority of the proposed SF-CNN method over several well-known classification methods, including pretrained CNN-based ones. 展开 关键词: Free-scale convolutional neural networks (CNNs) fully connected layers (FCLs) ...
Complex networks can be classified in three main types: random networks, small-world networks and scale-free networks. Two approaches are tested and compar... K Mahdi,M Safar,I Sorkhoh,... - 《Journal of Digital Information Management》 被引量: 17发表: 2009年 tool for classification of soc...
tissues, and various types of stress are required53,57,58. The more transcriptomes used, the better the statistical significance of the co-expression relationship between genes becomes. Furthermore, the diversity of transcriptomes makes it possible to identify specific networks for...
Subnets of scale-free networks are not scale-free: Sampling properties of networks Proceedings of the National Academy of Sciences of the United States of America, 102 (2005), pp. 4221-4224, 10.1073/pnas.0501179102 View in ScopusGoogle Scholar Sun, Wang, Yang, Liu, 2020a X. Sun, Z. Wang...
5.4.1.2Artificial Neural Networks Artificial Neural Networks are a commonly used method for several kinds of classification problems. It is basically constructed with an input layer, one or more hidden layers, and an output layer. The layers are made up of nodes; while the number of nodes in ...
[23,24,25] introduced small-world networks and scale-free properties into the reservoir structure of echo state networks to form a new kind of reservoir. Cui et al. [26] came out with three new dynamic reservoir topologies based on complex network theory for echo state networks, specifically...
of equilibrium points, owing to the large number of different kinds of possible topologies of large scale networks. Instead of theoretical proofs, often simulation and experimentation based proofs have been provided. One of the most important findings of this category of approaches is the lack of ...
have shown the effectiveness of the traffic classification process, where each one of them has its own strength and weakness.Deep learning algorithms, such as Convolution Neural Networks (CNN), have proven their efficiency through the unnecessity of extracting any statistical feature and through their...
Motor Imagery A deep CNN approach to decode motor preparation of upper limbs from time–frequency maps of EEG signals at source level CNN (CWT,TF) Neural Networks 2020 Motor Imagery Convolutional neural network based features for motor imagery EEG signals classification in brain–computer interface ...