Book contents
- Time Series Data Analysis in Oceanography
- Time Series Data Analysis in Oceanography
- Copyright page
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Introduction to MATLAB
- 3 Time and MATLAB Functions for Time
- 4 Deterministic and Random Functions
- 5 Error and Variability Propagation
- 6 Taylor Series Expansion and Application in Error Estimate
- 7 Spherical Trigonometry and Distance Computation
- 8 A System of Linear Equations and Least Squares Method
- 9 Base Functions and Linear Independence
- 10 Generic Least Squares Method and Orthogonal Functions
- 11 Harmonic Analysis of Tide
- 12 Fourier Series
- 13 Fourier Transform
- 14 Discrete Fourier Transform and Fast Fourier Transform
- 15 Properties of Fourier Transform
- 16 More Discussion on the Harmonic Analysis and Fourier Analysis
- 17 Effect of Finite Sampling
- 18 Power Spectrum, Cospectrum, and Coherence
- 19 Window Functions for Reducing Side Lobes
- 20 Convolution, Filtering with the Window Method
- 21 Digital Filters
- 22 Rotary Spectrum Analysis
- 23 Short-Time Fourier Transform and Introduction to Wavelet Analysis
- 24 Empirical Orthogonal Function Analysis
- References
- Index
18 - Power Spectrum, Cospectrum, and Coherence
Published online by Cambridge University Press: 21 April 2022
Book contents
- Time Series Data Analysis in Oceanography
- Time Series Data Analysis in Oceanography
- Copyright page
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Introduction to MATLAB
- 3 Time and MATLAB Functions for Time
- 4 Deterministic and Random Functions
- 5 Error and Variability Propagation
- 6 Taylor Series Expansion and Application in Error Estimate
- 7 Spherical Trigonometry and Distance Computation
- 8 A System of Linear Equations and Least Squares Method
- 9 Base Functions and Linear Independence
- 10 Generic Least Squares Method and Orthogonal Functions
- 11 Harmonic Analysis of Tide
- 12 Fourier Series
- 13 Fourier Transform
- 14 Discrete Fourier Transform and Fast Fourier Transform
- 15 Properties of Fourier Transform
- 16 More Discussion on the Harmonic Analysis and Fourier Analysis
- 17 Effect of Finite Sampling
- 18 Power Spectrum, Cospectrum, and Coherence
- 19 Window Functions for Reducing Side Lobes
- 20 Convolution, Filtering with the Window Method
- 21 Digital Filters
- 22 Rotary Spectrum Analysis
- 23 Short-Time Fourier Transform and Introduction to Wavelet Analysis
- 24 Empirical Orthogonal Function Analysis
- References
- Index
Summary
The objective of this chapter is to present some important relations between the Fourier Transform and correlation functions. It turns out that the cross-correlation function and autocorrelation function have some useful relationships to Fourier Transform and power spectrum of the individual functions. As a result, cospectrum and coherence (normalized statistical correlation in frequency domain) can be defined.
Keywords
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- Chapter
- Information
- Time Series Data Analysis in OceanographyApplications using MATLAB, pp. 331 - 347Publisher: Cambridge University PressPrint publication year: 2022