Introduction -- Preliminaries -- Methods of Estimation - Iterative -- Methods of Estimation - Non-iterative -- Asymptotic Results (of Sinusoidal model) -- Order estimation -- Fundamental Frequency Model and its generalization -- Data Analysis -- Two dimensional and multidimensional models -- Chirp Signal Model -- Random Amplitudes -- Related Models -- Appendices.

This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.