scholarly journals Transient Signal Feature Extraction Based on Box Dimension and the Largest Lyapunov Dimension

2012 ◽  
Author(s):  
Caidan Zhao ◽  
Fujia Yan ◽  
Minghui Gao ◽  
Lianfen Huang
Keyword(s):  
Feature Extraction ◽  
Transient Signal ◽  
Box Dimension ◽  
Lyapunov Dimension

Transient Signal Feature Extraction Based on Box Dimension and the Largest Lyapunov Dimension

2013 ◽  
Vol 756-759 ◽  
pp. 3607-3610
Author(s):  
Cai Dan Zhao ◽  
Fu Jia Yan ◽  
Ming Hui Gao ◽  
Lian Fen Huang
Keyword(s):  
Fractal Dimension ◽  
Wireless Communication ◽  
Primary User ◽  
Spectrum Efficiency ◽  
Transient Signal ◽  
Box Dimension ◽  
Security Issues ◽  
Primary User Emulation ◽  
Wireless Transmitter ◽  
Signal Characteristics

Cognitive radio is one kind of wireless communication technology, which is to effectively improve the spectrum efficiency by the way of wireless spectrum sensing. Besides of varieties of security issues of the traditional wireless communication, it also has some new problems, such as Primary User Emulation (PUE) attack. This essay presents that based on the fractal dimension of the transient signal characteristics extraction to protect the PUE attack from the cognitive wireless networks, and then extract the fractal dimension of wireless transmitter through experiments to provide reliable characteristic parameters for the next signal recognition, finally to prevent PUEs attack.

scholarly journals Non-Intrusive Load Monitoring Based on Novel Transient Signal in Household Appliances with Low Sampling Rate

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3409 ◽  
Author(s):  
Thi-Thu-Huong Le ◽  
Howon Kim
Keyword(s):  
Climate Change ◽  
Feature Extraction ◽  
Sampling Rate ◽  
Low Frequency ◽  
Classification Model ◽  
Transient Signal ◽  
Household Appliances ◽  
Positive Effects ◽  
Load Monitoring ◽  
Electrical Consumption

Nowadays climate change problems have been more and more concerns and urgent in the real world. Especially, the energy power consumption monitoring is a considerate trend having positive effects in decreasing affecting climate change. Non-Intrusive Load Monitoring (NILM) is the best economic solution to solve the electrical consumption monitoring issue. NILM captures the electrical signals from the aggregate energy consumption, feature extraction from these signals and then learning and predicting the switch ON/OFF of appliances used these feature extracted. This paper proposed a NILM framework including data acquisition, data feature extraction, and classification model. The main contribution is to develop a new transient signal in a different aspect. The proposed transient signal is extracted from the active power signal in the low-frequency sampling rate. This transient signal is used to detect the event of household appliances. In household appliances event detection, we applied to Decision Tree and Long Short-Time Memory (LSTM) models. The average accuracies of these models achieved 92.64% and 96.85%, respectively. The computational and result experiments present the solution effectiveness for the accurate transient signal extraction in the electrical input signals.

scholarly journals Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors

2018 ◽  
Vol 5 (5) ◽  
pp. 180087 ◽  
Author(s):  
Xiang Chen ◽  
Jingchao Li ◽  
Hui Han ◽  
Yulong Ying
Keyword(s):  
Feature Extraction ◽  
Hilbert Transform ◽  
Radiation Source ◽  
Box Dimension ◽  
Instantaneous Amplitude ◽  
Box Counting ◽  
Box Counting Dimension ◽  
Source Signal ◽  
The Hilbert Transform ◽  
Subtle Feature

Because of the limitations of the traditional fractal box-counting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension eigenvector algorithm is proposed. First, the radiation source signal was preprocessed, and a Hilbert transform was performed to obtain the instantaneous amplitude of the signal. Then, the improved fractal box-counting dimension of the signal instantaneous amplitude was extracted as the first eigenvector. At the same time, the improved fractal box-counting dimension of the signal without the Hilbert transform was extracted as the second eigenvector. Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the grey relation algorithm. The experimental results show that, compared with the traditional fractal box-counting dimension algorithm and the single improved fractal box-counting dimension algorithm, the proposed dual improved fractal box-counting dimension algorithm can better extract the signal subtle distribution characteristics under different reconstruction phase space, and has a better recognition effect with good real-time performance.

scholarly journals Data-Rate Constrained Observers of Nonlinear Systems

Entropy ◽  
2019 ◽  
Vol 21 (3) ◽  
pp. 282 ◽  
Author(s):  
Quentin Voortman ◽  
Alexander Pogromsky ◽  
Alexey Matveev ◽  
Henk Nijmeijer
Keyword(s):  
Dynamical System ◽  
Communication Channel ◽  
Lorenz System ◽  
Upper Bounds ◽  
Data Rate ◽  
The State ◽  
Box Dimension ◽  
Lyapunov Dimension ◽  
Remote Location ◽  
The Lorenz System

In this paper, the design of a data-rate constrained observer for a dynamical system is presented. This observer is designed to function both in discrete time and continuous time. The system is connected to a remote location via a communication channel which can transmit limited amounts of data per unit of time. The objective of the observer is to provide estimates of the state at the remote location through messages that are sent via the channel. The observer is designed such that it is robust toward losses in the communication channel. Upper bounds on the required communication rate to implement the observer are provided in terms of the upper box dimension of the state space and an upper bound on the largest singular value of the system’s Jacobian. Results that provide an analytical bound on the required minimum communication rate are then presented. These bounds are obtained by using the Lyapunov dimension of the dynamical system rather than the upper box dimension in the rate. The observer is tested through simulations for the Lozi map and the Lorenz system. For the Lozi map, the Lyapunov dimension is computed. For both systems, the theoretical bounds on the communication rate are compared to the simulated rates.

Experimental Research on the Feature Extraction of Underwater Transient Signal

2013 ◽  
Vol 572 ◽  
pp. 463-466
Author(s):  
Shi Jun Sun ◽  
Yang Li
Keyword(s):  
Feature Extraction ◽  
Theoretical Analysis ◽  
Experimental Research ◽  
Pulse Signal ◽  
Water Entry ◽  
Transient Signal ◽  
Water Splash

After the aerial object enters the water, splash sound forms. It composes of water entry pulse signal, quiet interval, and bubbles fluctuant signal. To extract the characteristics of the splash sound, characteristics of the three parts of the signal are analyzed in theoretically. And then experimental research is done, in which five different targets are adopted to be launched under different conditions. Comparing with the results of different conditions, we draw some conclusions which coincide with the theoretical analysis.

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