Geophysical Data Analysis book cover

Geophysical Data Analysis

Discrete Inverse Theory

Please use extracts from reviews of first edition

Audience
Graduate students and researchers in solid earth geophysics, seismology, atmospheric sciences and other areas of applied physics (e.g. image processing) and mathematics.

Included in series
International Geophysics

,

Published: August 1989

Imprint: Academic Press

ISBN: 978-0-12-490921-2

Reviews

  • "The author has produced a meaningful guide to the subject; one which a student (or professional unfamiliar with the field) can follow without great difficulty and one in which many motivational guideposts are provided....I think that the value of the book is outstanding....It deserves a prominent place on the shelf of every scientist or engineer who has data to interpret."
    --GEOPHYSICS


    "As a meteorologist, I have used least squares, maximum likelihood, maximum entropy, and empirical orthogonal functions during the course of my work, but this book brought together these somewhat disparate techniques into a coherent, unified package....I recommend it to meteorologists involved with data analysis and parameterization."
    --Roland B. Stull, THE BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
    "This book provides an excellent introductory account of inverse theory with geophysical applications....My experience in using this book, along with supplementary material in a course for the first year graduate students, has been very positive. I unhesitatingly recommend it to any student or researcher in the geophysical sciences."
    --PACEOPH

Contents

  • Intoduction. Describing Inverse Problems. Some Comments on Probability Theory. Solution of the Linear, Gaussian Inverse Problem, Viewpoint 1. The Length Method. Solution of the Linear, Gaussian Inverse Problem, Viewpoint 2. Generalized Inverses. Solution of the Linear, Gaussian Inverse Problem, Viewpoint 3. Maximum Likelihood Methods. Nonuniqueness and Localized Averages. Applications of Vector Spaces. Linear Inverse Problems and Non-Gaussian Distributions. Nonlinear Inverse Problems. Factor Analysis. Continuous Inverse Theory and Tomography. Sample Inverse Problems. Numerical Algorithms. Applications of Inverse Theory to Geophysics. Appendices. Implementing Constraints with Lagrange Multipliers. Inverse Theory with Complex Quantities. References. Index

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