Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques

Percival, Donald B. Donald B. Percival, Andrew T. Walden,

ISBN 10: 052135532X / ISBN 13: 9780521355322

Published by Cambridge University Press, 1993

About this Item

Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .

Seller Inventory # 7719-9780521355322

Bibliographic Details

• Title: Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques
• Publisher: Cambridge University Press
• Publication Date: 1993
• Language: English
• ISBN 10: 052135532X
• ISBN 13: 9780521355322
• Binding: hardcover
• Condition: Very Good

About this title

Synopsis

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.

Book Description

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.