ABSTRACT

Time series with mixed spectra are characterized by hidden periodic components buried in random noise. Despite strong interest in the statistical and signal processing communities, no book offers a comprehensive and up-to-date treatment of the subject. Filling this void, Time Series with Mixed Spectra focuses on the methods and theory for the stati

chapter 1|12 pages

Introduction

chapter 2|24 pages

Basic Concepts

chapter 3|38 pages

Cramér-Rao Lower Bound

chapter 4|36 pages

Autocovariance Function

chapter 5|56 pages

Linear Regression Analysis

chapter 6|86 pages

Fourier Analysis Approach

chapter 7|58 pages

Estimation of Noise Spectrum

chapter 8|64 pages

Maximum Likelihood Approach

chapter 9|80 pages

Autoregressive Approach

chapter 10|74 pages

Covariance Analysis Approach

chapter 11|38 pages

Further Topics

chapter 12|44 pages

Appendix