scholarly journals The rational connection coefficient calculation with different train structures

2020 ◽  
Vol 918 ◽  
pp. 012052
Author(s):  
Nurmukhammad Ya Makhkamov ◽  
Gulshan R Ibragimova ◽  
Azizbek F Ismatullaev
Keyword(s):  
Connection Coefficient

Analog Learning Neural Network using Two-Stage Mode by Multiple and Sample Hold Circuits

2014 ◽  
Vol 2 (1) ◽  
pp. 61-72 ◽  
Author(s):  
Masashi Kawaguchi ◽  
Naohiro Ishii ◽  
Takashi Jimbo
Keyword(s):  
Neural Network ◽  
Vision System ◽  
Network Models ◽  
Input Voltage ◽  
Neural Network Models ◽  
Artificial Retina ◽  
The Neural Network ◽  
Connection Coefficient ◽  
Retina Chip ◽  
Short Time

In the neural network field, many application models have been proposed. A neuro chip and an artificial retina chip are developed to comprise the neural network model and simulate the biomedical vision system. Previous analog neural network models were composed of the operational amplifier and fixed resistance. It is difficult to change the connection coefficient. In this study, we used analog electronic multiple and sample hold circuits. The connecting weights describe the input voltage. It is easy to change the connection coefficient. This model works only on analog electronic circuits. It can finish the learning process in a very short time and this model will enable more flexible learning.

scholarly journals Finding Central Vertices and Community Structure via Extended Density Peaks-Based Clustering

Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 501
Author(s):  
Yuanyuan Meng ◽  
Xiyu Liu
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
State Of The Art ◽  
Research Field ◽  
Community Centers ◽  
Density Peaks ◽  
Resolution Limits ◽  
Significant Research ◽  
Connection Coefficient ◽  
Real Community

Community detection is a significant research field of social networks, and modularity is a common method to measure the division of communities in social networks. Many classical algorithms obtain community partition by improving the modularity of the whole network. However, there is still a challenge in community division, which is that the traditional modularity optimization is difficult to avoid resolution limits. To a certain extent, the simple pursuit of improving modularity will cause the division to deviate from the real community structure. To overcome these defects, with the help of clustering ideas, we proposed a method to filter community centers by the relative connection coefficient between vertices, and we analyzed the community structure accordingly. We discuss how to define the relative connection coefficient between vertices, how to select the community centers, and how to divide the remaining vertices. Experiments on both real and synthetic networks demonstrated that our algorithm is effective compared with the state-of-the-art methods.

scholarly journals Evolution of Cryptocurrency: Changes in the Use and Consumer Demand for Digital Transactions

2021 ◽  
Vol 9 (10) ◽  
pp. 842-850
Author(s):  
Dr. Varsha Agarwal
Keyword(s):  
Correlation Analysis ◽  
Cross Correlation ◽  
Consumer Demand ◽  
Private Bank ◽  
The Past ◽  
Digital Currency ◽  
Air Pocket ◽  
Cross Correlation Analysis ◽  
Connection Coefficient ◽  
Digital Transactions

Abstract: The quick advancement of cryptographic forms of money has caused to notice this specific market, with financial backers attempting to comprehend its conduct and analysts attempting to clarify it. The development of digital currencies' costs showed a sort of air pocket and an accident toward the finish of 2017. In view of this occasion, and on the way that Bitcoin is the most perceived digital currency, we propose to assess the infection impact among Bitcoin and other significant cryptographic forms of money. Utilizing the Detrended Cross-Correlation Analysis connection coefficient and looking at the period after and before the accident, we discovered proof of an infection impact, with this specific market being more incorporated now than in the past something that ought to be considered by current and likely financial backers. Cryptocurrency like Bitcoin have developed from being related only with geeks and revolutionaries to being considered by national banks as an innovation to carry out advanced cash. Digital forms of money exist just in computerized shape and can be moved totally between advanced addresses. This is both not normal for traditional electronic cash as perceived by laypersons which goes about as an obligation guarantee on a store with a confided in monetary foundation, for example, a private bank and dissimilar to ordinary bodily cash which might be truly moved by. This implies that any lawful rights related with holding digital forms of money should be diverse in spite of it being staying not entirely clear. In this , we take a gander at the different medicines of cash in the lawful detect and talk about the dangers related with each by drawing on genuine models. We presume that extortion through hacking might actually represent an issue to broad reception of cryptographic forms of money as the shortfall of plan of action against an outsider, for example, a bank amasses hazard in holders of digital currencies. Clients should hence practice alert and comprehend the dangers prior to putting resources into digital currencies. This admonition requires accentuation as many gatherings misunderstand the cryptography inside the innovation as shielding them from such misrepresentation when truth be told it does nothing of the sort. Keywords: Cryptocurrency, Cryptography, Digital Currencies, Bitcoin, Blockchain.

Early Detection of Cyber Attacks Based on Feature Selection Algorithm

2020 ◽  
Vol 17 (9) ◽  
pp. 4648-4653
Author(s):  
J. Dayanika ◽  
G. Archana ◽  
K. Siva Kumar ◽  
N. Pavani
Keyword(s):  
Machine Learning ◽  
Cyber Attacks ◽  
Complex Nature ◽  
Selection Algorithm ◽  
Feature Selection Algorithm ◽  
Profound Knowledge ◽  
The World ◽  
Benchmark Datasets ◽  
Connection Coefficient ◽  
The Many

The world is turning out to be progressively digitalized raising security concerns and the urgent requirement for strong and propelled security advancements and systems to battle the expanding complex nature of digital assaults. This paper talks about how machine learning is being utilized in digital security in resistance and offense exercises, remembering conversations for digital assaults focused at machine learning models. In this review, we are proposing a scientific categorization of IDS, which considers information protests to be essential measurements to group and condense IDS Literature based on machine learning and based on profound knowledge. The review explains initially the idea and scientific grade of IDSs. Machine learning calculations are presented at that point for the many time used in IDSs, measurements and presented benchmark datasets. Next, we take the proposed ordered framework as a benchmark in conjunction with the agent writing and explain how to understand key IDS issues with machine learning and profound systems. At long last, difficulties and future advancements are talked about by assessing ongoing agent examines. This paper proposes IDS dependent on highlight determination and bunching calculation utilizing channel and wrapper techniques. Channel and wrapper strategies are named include gathering dependent on direct connection coefficient (FGLCC) calculation and cuttlefish calculation (CFA), separately.

scholarly journals Research on Transmission Network Expansion Planning Considering Splitting Control

2020 ◽  
Vol 12 (5) ◽  
pp. 1769
Author(s):  
Fei Tang ◽  
Chufei Xiao ◽  
Xin Gao ◽  
Yifan Zhang ◽  
Nianchun Du ◽  
...  
Keyword(s):  
Cross Section ◽  
Programming Model ◽  
Power Grid ◽  
Network Planning ◽  
Adaptive Mutation ◽  
Transmission Network ◽  
Monitoring Method ◽  
Expansion Planning ◽  
Core Elements ◽  
Connection Coefficient

A robust and reliable grid is one of the core elements for power network planning. Specifically, splitting is an effective way for power grid out-of-step oscillation. Since the cross-section of system out-of-step is mostly found on the weak connection lines, reducing the number of those lines can be conducive to the system partition, save the finding time of the optimal splitting cross-section, and improve the performance of the splitting control. This paper proposed an enhanced method based on slow coherence theory for weak connection lines’ identification and monitoring. The ratio of the number of weak connection lines to the number of all the lines, called weak connection coefficient, is considered as a crucial factor. A bi-level programming model, which perceives the minimum connection coefficient as the optimization goal, is built for the transmission network. Additionally, a fused algorithm, consisting of Boruvka algorithm and particle swarm optimization with adaptive mutation and inertia weight, is employed to solve the proposed method in the instances of an 18-node IEEE Graver system and a practical power grid in East China. Simulation results in PSD-BPA are conducted to verify the effectiveness of the weak connection monitoring method and transmission network planning model.

scholarly journals Forces in the complex octonion curved space

2016 ◽  
Vol 13 (06) ◽  
pp. 1650076 ◽  
Author(s):  
Zi-Hua Weng
Keyword(s):  
Covariant Derivative ◽  
Flat Space ◽  
Gravitational Theory ◽  
Electromagnetic Theory ◽  
Field Source ◽  
Curved Space ◽  
Gravitational Fields ◽  
Gravitational Theories ◽  
Complex Quaternion ◽  
Connection Coefficient

The paper aims to extend major equations in the electromagnetic and gravitational theories from the flat space into the complex octonion curved space. Maxwell applied simultaneously the quaternion analysis and vector terminology to describe the electromagnetic theory. It inspires subsequent scholars to study the electromagnetic and gravitational theories with the complex quaternions/octonions. Furthermore Einstein was the first to depict the gravitational theory by means of tensor analysis and curved four-space–time. Nowadays some scholars investigate the electromagnetic and gravitational properties making use of the complex quaternion/octonion curved space. From the orthogonality of two complex quaternions, it is possible to define the covariant derivative of the complex quaternion curved space, describing the gravitational properties in the complex quaternion curved space. Further it is possible to define the covariant derivative of the complex octonion curved space by means of the orthogonality of two complex octonions, depicting simultaneously the electromagnetic and gravitational properties in the complex octonion curved space. The result reveals that the connection coefficient and curvature of the complex octonion curved space will exert an influence on the field strength and field source of the electromagnetic and gravitational fields, impacting the linear momentum, angular momentum, torque, energy, and force and so forth.

scholarly journals Quadratic $q$-exponentials and connection coefficient problems

1999 ◽  
Vol 127 (10) ◽  
pp. 2931-2941 ◽  
Author(s):  
Mourad E. H. Ismail ◽  
Mizan Rahman ◽  
Dennis Stanton
Keyword(s):  
Connection Coefficient ◽  
Coefficient Problems
Sign in / Sign up

Export Citation Format

Share Document