CHAPTER 1: STOCHASTIC PROCESSES
1. Introducing Ordered Data
2. Stationary Processes and Autocovariance
3. White Noises and their Relatives
4. Examples from the Real World
CHAPTER 2: SPECTRAL ANALYSIS OF STOCHASTIC PROCESSES
1. Spectral Analysis
2. Two Definitions of the PSD
3. Some Properties of the PSD
4. PSD of Discrete Processes
5. Aliasing in the PSD
6. Illustrations
Appendix: Proof of Equation (2.20)
CHAPTER 3: ESTIMATING THE POWER SPECTRAL DENSITY
1. Introduction
2. Several Bad Approaches
3. The Raw Periodogram: White Gaussian Noise
4. The Raw Periodogram: Continuous Spectra
5. Simple Fixes for the Periodogram
6. The Perfect Taper
7. Spectral Estimation: Multitapers
8. Local Bias Minimization
9. Prewhitening
References
CHAPTER 4: MULTIVARIATE AND MULTIDIMENSIONAL SPECTRA
1. Random Data Pairs
2. Pairs of Stationary Signals
3. Estimation of Cross Spectra (Briefly)
4. Example: Calibration - Convolution plus Noise
5. Stationary Processes in the Plane
6. Example: Magnetics over the Ocean
7. Stationary Processes on a Sphere
References