Preface

Geophysics ◽  
1967 ◽  
Vol 32 (3) ◽  
pp. 414-414
Author(s):  
Daniel Silverman
Keyword(s):  
Time Series ◽  
Small Group ◽  
Statistical Methods ◽  
Seismic Data ◽  
Communication Theory ◽  
Digital Processing ◽  
Communications Industry ◽  
Methods Of Analysis ◽  
Standard Operating ◽  
Analysis Of Time Series

In recent years there has been a great surge of interest in the geophysical industry in the digital processing of seismic data. This activity involves the application of statistical methods of analysis of time series. In a way it is a part of the general subject of communication theory. However, the direction this work has taken is in many respects quite divergent from communication theory as it is used in the communications industry. The divergence is so great, in fact, that if it were not for a small group of workers in this field in the early 1950's, it is doubtful whether we would today be in a position to do what is now rapidly becoming standard operating practice in the geophysical industry.

Asteroseismic Data Analysis

2017 ◽  
Author(s):  
Sarbani Basu ◽  
William J. Chaplin
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Seismic Data ◽  
Stellar Populations ◽  
Instruction Manual ◽  
Kepler Mission ◽  
Cool Stars ◽  
Internal Properties ◽  
Analysis Of Time Series

Studies of stars and stellar populations, and the discovery and characterization of exoplanets, are being revolutionized by new satellite and telescope observations of unprecedented quality and scope. Some of the most significant advances have been in the field of asteroseismology, the study of stars by observation of their oscillations. This book gives a comprehensive technical introduction to this discipline. It not only helps students and researchers learn about asteroseismology; it also serves as an essential instruction manual for those entering the field. The book presents readers with the foundational techniques used in the analysis and interpretation of asteroseismic data on cool stars that show solar-like oscillations. The techniques have been refined, and in some cases developed, to analyze asteroseismic data collected by the NASA Kepler mission. Topics range from the analysis of time-series observations to extract seismic data for stars to the use of those data to determine global and internal properties of the stars. Reading lists and problem sets are provided, and data necessary for the problem sets are available online.

THE DIGITAL PROCESSING OF SEISMIC DATA

Geophysics ◽  
1967 ◽  
Vol 32 (6) ◽  
pp. 988-1002 ◽  
Author(s):  
Daniel Silverman
Keyword(s):  
Seismic Data ◽  
Communication Theory ◽  
Digital Filtering ◽  
Digital Processing ◽  
Wiener Filtering ◽  
Seismic Process ◽  
Field Recording ◽  
Noise Characteristics ◽  
Velocity Filtering

The paper discusses the background of the problem of signal and noise in the seismic process, and the application of the principles of communication theory to this problem. The limitations of the seismic process are discussed along with the types of noises involved, the methods of rejecting noise, the use of filters to reduce noise, characteristics of filters, and the relationships between frequency domain, time domain, mathematical, and digital filters. In the discussion of the electronic data processing of seismic information, the characteristics of an ideal seismic digital computer system are developed in relation to the characteristics of seismic data. The choice between digital and analog field recording is discussed in relation to the needs of the seismic process and the quality of the seismic data. Among the mathematical processes discussed are velocity filtering and a number of types of Wiener filtering, including horizontal stacking, deghosting, deconvolution, and multitrace digital filtering.

Correlation in the heart rate data

1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Heart Rate ◽  
Time Series ◽  
Cardiovascular Function ◽  
Statistical Properties ◽  
Rate Data ◽  
Heart Rate Data ◽  
Dynamical Nature ◽  
Analysis Of Time Series

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.

scholarly journals Interpretation of the Chemical and Physical Time-Series Retrieved from Sentik Glacier, Ladakh Himalaya, India

1984 ◽  
Vol 30 (104) ◽  
pp. 66-76 ◽  
Author(s):  
Paul A. Mayewski ◽  
W. Berry Lyons ◽  
N. Ahmad ◽  
Gordon Smith ◽  
M. Pourchet
Keyword(s):  
Time Series ◽  
Chemical Species ◽  
Data Sets ◽  
Reactive Iron ◽  
Physical Time ◽  
Ladakh Himalaya ◽  
Data Density ◽  
Mass Circulation ◽  
The Himalaya ◽  
Analysis Of Time Series

AbstractSpectral analysis of time series of a c. 17 ± 0.3 year core, calibrated for total ß activity recovered from Sentik Glacier (4908m) Ladakh, Himalaya, yields several recognizable periodicities including subannual, annual, and multi-annual. The time-series, include both chemical data (chloride, sodium, reactive iron, reactive silicate, reactive phosphate, ammonium, δD, δ(18O) and pH) and physical data (density, debris and ice-band locations, and microparticles in size grades 0.50 to 12.70 μm). Source areas for chemical species investigated and general air-mass circulation defined from chemical and physical time-series are discussed to demonstrate the potential of such studies in the development of paleometeorological data sets from remote high-alpine glacierized sites such as the Himalaya.

scholarly journals Low-Pass Filtering Method for Poisson Data Time Series

2021 ◽  
Vol 11 (10) ◽  
pp. 4524
Author(s):  
Victor Getmanov ◽  
Vladislav Chinkin ◽  
Roman Sidorov ◽  
Alexei Gvishiani ◽  
Mikhail Dobrovolsky ◽  
...  
Keyword(s):  
Time Series ◽  
Finite Impulse Response ◽  
Digital Processing ◽  
Distributed Data ◽  
Gaussian Filter ◽  
Experimental Physics ◽  
Filtering Method ◽  
Filter Synthesis ◽  
Low Pass ◽  
Poisson Data

Problems of digital processing of Poisson-distributed data time series from various counters of radiation particles, photons, slow neutrons etc. are relevant for experimental physics and measuring technology. A low-pass filtering method for normalized Poisson-distributed data time series is proposed. A digital quasi-Gaussian filter is designed, with a finite impulse response and non-negative weights. The quasi-Gaussian filter synthesis is implemented using the technology of stochastic global minimization and modification of the annealing simulation algorithm. The results of testing the filtering method and the quasi-Gaussian filter on model and experimental normalized Poisson data from the URAGAN muon hodoscope, that have confirmed their effectiveness, are presented.

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