This book is an up-to-date introduction to univariate spectral analysis aimed at graduate students, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. It gives equal weight to both algorithms and statistical theory and is valuable for the many examples it gives showing the application of spectral analysis to real data sets. The book is unique in placing special emphasis on the multitaper technique, which can successfully handle spectra with intricate structure and data with or without spectral lines. The text contains a large number of exercises.

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This up-to-date introduction to univariate spectral analysis at the graduate level reflects a new scientific awareness of its complexity, as well as its widespread usage on digital computers with considerable computational power.

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