scholarly journals Analysis of geoacoustic emission and electromagnetic radiation signals accompanying earthquake with magnitude Mw = 7.5

2020 ◽  
Vol 196 ◽  
pp. 03001
Author(s):  
Olga Lukovenkova ◽  
Alexandra Solodchuk
Keyword(s):  
Electromagnetic Radiation ◽  
Frequency Spectrum ◽  
Matching Pursuit ◽  
Kamchatka Peninsula ◽  
Pulse Waveform ◽  
Frequency Spectra ◽  
Pulse Detection ◽  
Geoacoustic Emission ◽  
Matching Pursuit Algorithm ◽  
Electromagnetic Signals

The paper is devoted to the analysis of frequency spectra and pulse waveform variety of the geoacoustic and electromagnetic signals recorded on Kamchatka Peninsula at “Karymshina” site during seismically calm and active periods. Signal pre-processing includes pulse detection and their waveforms reconstruction. A frequency spectrum is analyzed using the Adaptive Matching Pursuit algorithm. To study a variety of waveforms, each pulse is encoded by a special descriptive matrix. Then pulse classification based on similarity of the descriptive matrices is performed. Thus, a signal alphabet is formed. The authors analyzed the geophysical signals recorded before, during and after the earthquake with the magnitude Mw = 7.5 dated March 25, 2020. The obtained estimates of frequency spectra and signal alphabets are compared with the analysis results of signal recoded during the seismically calm period of March 22, 2020.

scholarly journals Modernization of adaptive matching pursuit method to analyze geophysical signals of pulse nature

2018 ◽  
Vol 62 ◽  
pp. 02012 ◽  
Author(s):  
Ol’ga Lukovenkova ◽  
Yuriy Marapulets ◽  
Aleksandr Tristanov ◽  
Alina Kim
Keyword(s):  
Numerical Methods ◽  
Matching Pursuit ◽  
Sparse Approximation ◽  
Approximation Methods ◽  
Initial Signal ◽  
Gradient Direction ◽  
Adaptive Property ◽  
Matching Pursuit Algorithm ◽  
Electromagnetic Signals ◽  
Direction Search

The paper is devoted to the development and comparison of different numerical methods which increase the adaptive property and improve the accuracy of matching pursuit algorithm in connection to geoacoustic and electromagnetic signals. At each step of adaptive matching pursuit, a function is chosen which has the highest correlation with an initial signal. Then parameters of a chosen function are refined. The refinement is performed by the help of different grid methods and methods based on gradient direction search. The paper considers the peculiarities of application of sparse approximation methods to geophysical signals of pulse nature and compares different variants of modification of adaptive matching pursuit algorithm.

scholarly journals Overview of processing and analysis methods for pulse geophysical signals

2020 ◽  
Vol 196 ◽  
pp. 02023
Author(s):  
Olga Lukovenkova ◽  
Yury Senkevich ◽  
Alexandra Solodchuk ◽  
Albert Shcherbina
Keyword(s):  
Matching Pursuit ◽  
Electromagnetic Emission ◽  
Kamchatka Peninsula ◽  
Threshold Scheme ◽  
Structural Description ◽  
Pulse Waveform ◽  
Time Frequency ◽  
Process Dynamics ◽  
Analysis Methods ◽  
Pulse Structure

The paper discusses the processing and analysis methods for the geoacoustic and electromagnetic emission pulse signals recorded for more than 20 years at the IKIR FEB RAS geodynamic proving ground (Kamchatka Peninsula). The methods for pulse detection, waveform reconstruction, pulse time-frequency analysis using adaptive sparse approximation, structural description of pulse waveforms and pulse classification are proposed. To detect pulses, the adaptive threshold scheme is used. It adjusts to the noise level of a processed signal. To analyze time-frequency structure of the pulses, the adaptive matching pursuit algorithm is used. To identify pulse waveform, the structural description method is proposed. It encodes pulses with special image matrices. The method of the identified pulses classification is considered. Since the methods for pulse structure analysis are sensitive to noise and distortions, the authors propose the method for pulse waveform reconstruction based on wavelet filtering. The geophysical signal information features determined during the analysis can be used to search for anomalies in the data, and then establish a relationship between these anomalies and deformation process dynamics, in particular, with earthquake development processes.

scholarly journals A Broadband Spectrum Sensing Algorithm in TDCS Based on ICoSaMP Reconstruction

2018 ◽  
Vol 173 ◽  
pp. 03073
Author(s):  
Liu Yang ◽  
Ren Qinghua ◽  
Xu Bingzheng ◽  
Li Xiazhao
Keyword(s):  
Time Use ◽  
Matching Pursuit ◽  
Reconstruction Algorithm ◽  
Transform Domain ◽  
Low Snr ◽  
System Noise ◽  
Broadband Spectrum ◽  
Matching Pursuit Algorithm ◽  
The Mean ◽  
Occupancy Rates

In order to solve the problem that the wideband compressive sensing reconstruction algorithm cannot accurately recover the signal under the condition of blind sparsity in the low SNR environment of the transform domain communication system. This paper use band occupancy rates to estimate sparseness roughly, at the same time, use the residual ratio threshold as iteration termination condition to reduce the influence of the system noise. Therefore, an ICoSaMP(Improved Compressive Sampling Matching Pursuit) algorithm is proposed. The simulation results show that compared with CoSaMP algorithm, the ICoSaMP algorithm increases the probability of reconstruction under the same SNR environment and the same sparse degree. The mean square error under the blind sparsity is reduced.

Incipient Broken Rotor Bar Detection in Induction Motors Using Vibration Signals and the Orthogonal Matching Pursuit Algorithm

2018 ◽  
Vol 67 (9) ◽  
pp. 2058-2068 ◽  
Author(s):  
Carlos Morales-Perez ◽  
Jose Rangel-Magdaleno ◽  
Hayde Peregrina-Barreto ◽  
Juan Pablo Amezquita-Sanchez ◽  
Martin Valtierra-Rodriguez
Keyword(s):  
Induction Motors ◽  
Matching Pursuit ◽  
Orthogonal Matching Pursuit ◽  
Vibration Signals ◽  
Broken Rotor Bar ◽  
Matching Pursuit Algorithm

scholarly journals Floristic, frequency, and vegetation life-form spectra of a cerrado site

2004 ◽  
Vol 64 (2) ◽  
pp. 201-209 ◽  
Author(s):  
M. A. Batalha ◽  
F. R. Martins
Keyword(s):  
Frequency Spectrum ◽  
Vascular Plants ◽  
Life Form ◽  
Quantitative Description ◽  
Life Forms ◽  
Sensu Stricto ◽  
Southeastern Brazil ◽  
Frequency Spectra ◽  
Experimental Station ◽  
Normal Spectrum

We used Raunkiaer's system to classify in life-forms the vascular plants present in 12 random 25 m² quadrats of a cerrado site. The study area is covered by cerrado sensu stricto and is located in the Valério fragment, at about 22º13'S and 47º51'W, 760 m above sea level, in the Itirapina Ecological and Experimental Station, São Paulo State, southeastern Brazil. The floristic spectrum considers the life-form of each species, while in the frequency spectrum, each species is weighted by its frequency. The vegetation spectrum does not consider the species at all, but only the individuals in each life-form class. In the floristic spectrum, the most represented life-forms were the phanerophytes and the hemicryptophytes, as in other cerrado sites. This spectrum differed significantly from Raunkiaer's normal spectrum, mainly due to under-representation of therophytes and over-representation of phanerophytes. The floristic and frequency spectra were similar, but both differed from the vegetation spectrum. We recommend the floristic spectrum when working at larger scales and a description of the phytoclimate is wanted. The vegetation spectrum is preferable when working at smaller scales and wanting a quantitative description of the physiognomy. The frequency spectrum is not recommended at all.

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