Maximum Entropy Spectral Analysis of Time-Series Data from Combustion MHD Plasma

1985 ◽  
Vol 24 (Part 1, No. 9) ◽  
pp. 1204-1211 ◽  
Author(s):  
Tadashi Seidou ◽  
Yoshiaki Aoki ◽  
Norio Ohtomo
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Maximum Entropy ◽  
Time Series Data ◽  
Series Data ◽  
Maximum Entropy Spectral Analysis ◽  
Analysis Of Time Series

scholarly journals PERAMALAN CURAH HUJAN MENGGUNAKAN METODE ANALISIS SPEKTRAL

2016 ◽  
Vol 5 (4) ◽  
pp. 183
Author(s):  
NI PUTU MIRAH SRI WAHYUNI ◽  
I WAYAN SUMARJAYA ◽  
I GUSTI AYU MADE SRINADI
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Complete Information ◽  
Series Data ◽  
Analysis Method ◽  
Maximum Rainfall ◽  
Spectral Analysis Method ◽  
Large Peak ◽  
Analysis Of Time Series

The purpose of this research is the model of forecasting rainfall using spectral analysis method. To obtain complete information on characteristics of time series data we need to examine periodicity of the data. Examining the periodicity of time series data in the frequency domain is called spectral analysis. The results of spectral analysis show that periodogram is clearly dominated by a very large peak at frequency . This frequency corresponds to period of 12 cycle per month. Based on the results of analysis of time series data rainfall is SARIMA (0,1,1)(0,1,1)12 where the model can be written as The result indicates minimum rainfall happen in January and maximum rainfall happen in August.

Spectral Analysis of Time-series Data

Technometrics ◽  
2004 ◽  
Vol 46 (4) ◽  
pp. 497-498
Author(s):  
Eric R Ziegel
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Of Time Series

Comprehensive Spectral Analysis of Time Series Data of Recurrent Epidemics

1997 ◽  
Vol 36 (Part 1, No. 3A) ◽  
pp. 1303-1318 ◽  
Author(s):  
Ayako Sumi ◽  
Norio Ohtomo ◽  
Yukio Tanaka ◽  
Akio Koyama ◽  
Kazuo Saito
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Analysis Of Time Series

scholarly journals The bird's ear view of space physics: Audification as a tool for the spectral analysis of time series data

2014 ◽  
Vol 119 (7) ◽  
pp. 5259-5271 ◽  
Author(s):  
Robert L. Alexander ◽  
Sile O'Modhrain ◽  
D. Aaron Roberts ◽  
Jason A. Gilbert ◽  
Thomas H. Zurbuchen
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Space Physics ◽  
Series Data ◽  
Analysis Of Time Series

MAXIMUM‐ENTROPY SPATIAL PROCESSING OF ARRAY DATA

Geophysics ◽  
1974 ◽  
Vol 39 (6) ◽  
pp. 843-851 ◽  
Author(s):  
R. N. McDonough
Keyword(s):  
Spectral Analysis ◽  
Maximum Entropy ◽  
Communication Theory ◽  
Model Building ◽  
Time Series Data ◽  
Series Data ◽  
Maximum Entropy Spectral Analysis ◽  
Predictive Deconvolution ◽  
Line Array ◽  
Spatially Distributed

The procedure of maximum‐entropy spectral analysis (MESA), used in the processing of time series data, also applies to wavenumber (bearing) analysis of signals received from a spatially distributed linear array of sensors. The method is precisely the use of autoregressive spectral analysis in the space dimension rather than in time. There are also close links to the predictive deconvolution method used in geophysical work, and to the process of constructing noise‐whitening filters in communication theory, as well as to least‐squares model building. In this note, we review the maximum‐entropy procedure pointing out all these links. The specific algorithm appropriate to a uniformly spaced line array of sensors is given, as well as one possible algorithm for use in the case of nonuniform sensor spacing.

scholarly journals SPAN: An interactive BASIC program for spectral analysis of time-series data

1980 ◽  
Vol 12 (3) ◽  
pp. 389-390
Author(s):  
Rebecca M. Warner ◽  
Paul G. Neumann
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Time Series Data ◽  
Basic Program ◽  
Series Data ◽  
Analysis Of Time Series
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