Recognition Method of Abnormal Data in Local Area Network Common Channel Based on Convolutional Neural Network

2021 ◽  
pp. 45-52
Author(s):  
Weiwei Lin ◽  
Sisheng Chen ◽  
Xingsi Xue ◽  
Reiko Haga
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Local Area Network ◽  
Local Area ◽  
Area Network ◽  
Common Channel ◽  
Recognition Method

scholarly journals Channel Path-Loss Measurement and Modeling in Wireless Data Network (IEEE 802.11n) Using Artificial Neural Network

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Olasoji Y. Olajide ◽  
Samson Musa Yerima
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Network Planning ◽  
Path Loss ◽  
Local Area ◽  
Line Of Sight ◽  
Area Network ◽  
Artificial Neural

Careful network planning has become increasingly critical with the rising deployment, coverage, and congestion of wireless local area networks (WLANs).This paper  investigates and determine the Path-loss exponent value for the ubiquitous wireless local area network at the Federal University Oye-Ekiti for the line of sight and non-line of sight (N-LOS). Aside this, the paper also models the wireless network using artificial neural network (ANN) technology by training some neurons based on data collected from a drive-test. The proposed ANN model performed with accuracy and is offered as a simple, yet strong predictive model for network planning – having both speed and accuracy. Results show, that for the area under study, Oye Campus has a higher   standard deviation of 5.76dBm as against ikole Campus with 1.44dBm, this is because of dense vegetation at Oye Campus. In view of this, the paper provides a predictive site survey for rapid wireless Access point deployment.

scholarly journals Development of Compound Fault Diagnosis System for Gearbox Based on Convolutional Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6169
Author(s):  
Ming-Chang Lin ◽  
Po-Yu Han ◽  
Yi-Hua Fan ◽  
Chih-Hung G. Li
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Local Area Network ◽  
Mechanical Equipment ◽  
Area Network ◽  
Diagnosis System ◽  
Training Time ◽  
Convolution Kernels ◽  
Fault Diagnosis System

Gear transmission is widely used in mechanical equipment. In practice, if the gearbox is damaged, it not only affects the yield rate but also damages other parts of machines; thus, increases the cost and difficulty of maintenance. With the advancement of technology, the concept of unmanned factories has been proposed; an automatic diagnosis system for the health management of gearboxes becomes necessary. In this paper, a compound fault diagnosis system for the gearbox based on convolutional neural network (CNN) is developed. Specifically, three-axis vibration signals measured by accelerometers are used as the input of the one-dimensional CNN; the detection of the existence and type of the fault is directly output. In testing, the model achieved nearly 100% accuracy on the fault samples we captured. Experimental evidence also shows that the frequency-domain data can provide better diagnostic results than the time-domain data due to the stable characteristics in the frequency spectrum. For practical usage, we demonstrated a remote fault diagnosis system through a local area network on an embedded platform. Furthermore, optimization of convolution kernels was also investigated. When moderately reducing the number of convolution kernels, it does not affect the diagnostic accuracy but greatly reduces the training time of the model.

scholarly journals Joint Timing and Frequency Synchronization Using Convolutional Neural Network in WLAN Systems

2021 ◽  
Vol 12 (6) ◽  
pp. 531-537
Author(s):  
Eui-Soo Lee Et.al
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Frequency Offset ◽  
Area Network ◽  
Ofdm Systems ◽  
Frequency Offsets

In wireless communication systems, the performance of the receiver is very sensitive to time and frequency offsets. In particular, orthogonal frequency division multiplexing (OFDM) systems are highly vulnerable to those offsets due to inter-carrier interference (ICI) and inter-symbol interference (ISI). To solve this problem, wireless local area network (WLAN) systems transmit a preamble for synchronization. In this paper, we propose a joint time and frequency offsets estimation technique based on convolutional neural network (CNN) for WLAN systems. In the proposed technique, the correlation between the received signal and the transmitted preamble is performed first. Then the frequency offset is coarsely compensated by several hypothesized offsets. The compensated signals are inputted to the proposed CNN and the CNN predicts the time and frequency offsets. The estimation performance is examined through computer simulation. According to the results, the proposed time offset estimator shows 3 dB to 6 dB performance gain, and the frequency offset estimator shows much lower root mean square error (RMSE) performance than the conventional technique at low SNRs

Strathnet—a local area network

1981 ◽  
Vol 1 (1) ◽  
pp. 21 ◽  
Author(s):  
David Hutchison ◽  
Doug Shepherd
Keyword(s):  
Local Area Network ◽  
Local Area ◽  
Area Network

A Local Area Network for Medical Research; Planning, Realization and Experience

1991 ◽  
Vol 30 (01) ◽  
pp. 53-64 ◽  
Author(s):  
R. Schosser ◽  
C. Weiss ◽  
K. Messmer
Keyword(s):  
Medical Research ◽  
Word Processing ◽  
Local Area Network ◽  
Local Area ◽  
Area Network ◽  
Test Installation ◽  
Cost Performance ◽  
The Public ◽  
On Line ◽  
The University

This report focusses on the planning and realization of an interdisciplinary local area network (LAN) for medical research at the University of Heidelberg. After a detailed requirements analysis, several networks were evaluated by means of a test installation, and a cost-performance analysis was carried out. At present, the LAN connects 45 (IBM-compatible) PCs, several heterogeneous mainframes (IBM, DEC and Siemens) and provides access to the public X.25 network and to wide-area networks for research (EARN, BITNET). The network supports application software that is frequently needed in medical research (word processing, statistics, graphics, literature databases and services, etc.). Compliance with existing “official” (e.g., IEEE 802.3) and “de facto” standards (e.g., PostScript) was considered to be extremely important for the selection of both hardware and software. Customized programs were developed to improve access control, user interface and on-line help. Wide acceptance of the LAN was achieved through extensive education and maintenance facilities, e.g., teaching courses, customized manuals and a hotline service. Since requirements of clinical routine differ substantially from medical research needs, two separate networks (with a gateway in between) are proposed as a solution to optimally satisfy the users’ demands.

Link-Level Simulator for Wireless local Area Network

2018 ◽  
Vol 6 (7) ◽  
pp. 314
Author(s):  
Chaithra. H. U ◽  
Vani H.R
Keyword(s):  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area Networks ◽  
Local Area ◽  
Long Term Evolution ◽  
Wireless Local Area Networks ◽  
Area Network ◽  
Network Simulator ◽  
Term Evolution

Now a days in Wireless Local Area Networks (WLANs) used in different fields because its well-suited simulator and higher flexibility. The concept of WLAN  with  advanced 5th Generation technologies, related to a Internet-of-Thing (IOT). In this project, representing the Network Simulator (NS-2) used linked-level simulators for Wireless Local Area Networks and still utilized IEEE 802.11g/n/ac with advanced IEEE 802.11ah/af technology. Realization of the whole Wireless Local Area Networking linked-level simulators inspired by the recognized Vienna Long Term Evolution- simulators. As a outcome, this is achieved to link together that simulator to detailed performances of Wireless Local Area Networking with Long Term Evolution, operated in the similar RF bands. From the advanced 5th Generation support cellular networking, such explore is main because different coexistences scenario can arise linking wireless communicating system to the ISM and UHF bands.

PERANCANGAN ANTENA MIKROSTRIPRECTANGULAR

Jurnal Teknik ◽  
2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Heru Abrianto
Keyword(s):  
Dielectric Constant ◽  
Patch Antenna ◽  
Wireless Lan ◽  
Microstrip Antenna ◽  
Wireless Local Area Network ◽  
Local Area Network ◽  
Local Area ◽  
Area Network ◽  
Dual Polarization ◽  
Feeding Technique

Microstrip antenna which designed with dual feeding at 2.4 GHz and 5.8 GHz can meet WLAN (Wireless Local Area Network) application.Antenna fabrication use PCB FR4 double layer with thickness 1.6 mm and dielectric constant value 4.4. The length of patch antenna according to calculation 28.63 mm, but to get needed parameter length of patch should be optimized to 53 mm. After examination, this antenna has VSWR 1.212 at 2.42 GHz and 1.502 at 5.8 GHz, RL -13.94 dB at 2.42 GHz and -20.357 dB at 5.8 GHz, gain of antenna 6.16 dB at 2.42 GHz and 6.91 dB at 5.8 GHz, the radiation pattern is bidirectional. Keywords : microstrip antenna, wireless LAN, dual polarization, single feeding technique

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