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Time Series Data Analysis in Oceanography. Applications Using MATLAB
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- Nombre de pages465
- FormatGrand Format
- PrésentationRelié
- Poids1.015 kg
- Dimensions17,5 cm × 25,0 cm × 3,0 cm
- ISBN978-1-108-47427-6
- EAN9781108474276
- Date de parution05/04/2022
- ÉditeurCambridge University Press
Résumé
Chunyan Li is a course instructor with years of experience in teaching physical oceanography, estuarine dynamics, weather analysis, calculus, and time series analysis. This book is for students and researchers interested in oceanography and other subjects in the Earth sciences who are looking for complete coverage of the theory and practice of time series data analysis using MATLAB. This textbook provides an introduction to the topic's core theory with examples and exercises, many drawn directly from the author's own teaching and research experiences.
The book discusses many concepts, including time ; distance on Earth ; wind, current, and wave data formats ; finding a subset of moving platform-based data along planned or random transects ; error propagation ; Taylor series expansion for error estimates ; the least squares method ; base functions and linear independence of base functions ; tidal harmonic analysis ; Fourier series and the generalized Fourier transform ; discrete Fourier transform and fast Fourier transform ; power spectrum, cospectrum, and coherence ; convolution and digital filtering techniques ; sampling theorems ; finite sampling effects, window functions, and reduction of side lobe effects ; rotary spectrum analysis for velocity vector time series ; short-term Fourier transform ; wavelet analysis ; and EOF analysis.
The book discusses many concepts, including time ; distance on Earth ; wind, current, and wave data formats ; finding a subset of moving platform-based data along planned or random transects ; error propagation ; Taylor series expansion for error estimates ; the least squares method ; base functions and linear independence of base functions ; tidal harmonic analysis ; Fourier series and the generalized Fourier transform ; discrete Fourier transform and fast Fourier transform ; power spectrum, cospectrum, and coherence ; convolution and digital filtering techniques ; sampling theorems ; finite sampling effects, window functions, and reduction of side lobe effects ; rotary spectrum analysis for velocity vector time series ; short-term Fourier transform ; wavelet analysis ; and EOF analysis.
