Information-based inversion and processing with applications

Information-based inversion and processing with applications /

This book examines different classical and modern aspects of geophysical data processing and inversion with emphasis on the processing of seismic records in applied seismology. Chapter 1 introduces basic concepts including: probability theory (expectation operator and ensemble statistics), elementar...

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Bibliographic Details
Online Access: Full text (MCPHS users only)
Main Author: Ulrych, Tadeusz J.
Other Authors: Sacchi, Mauricio D.
Format: Electronic eBook
Language:English
Published: Amsterdam ; Boston : Elsevier, 2005
Edition:1st ed.
Series:Handbook of geophysical exploration. Seismic exploration ; v. 36.
Subjects:
Inversion (Geophysics)
dissertations.
Academic theses.
Local Note:ProQuest Ebook Central
Table of Contents:
  • Cover
  • Contents
  • Some Basic Concepts
  • Introduction
  • Probability Distributions, Stationarity & Ensemble Statistics
  • Properties of Estimators
  • Orthogonality
  • Orthogonal Vector Space
  • Fourier Analysis
  • Expectations etc.,
  • Lagrange Multipliers
  • Linear Time Series Modelling
  • Introduction
  • The Wold Decomposition Theorem
  • The Moving Average. MA, Model
  • The Autoregressive, AR, Model
  • The Autoregressive Moving Average, ARMA, Model
  • MA, AR and ARMA Models in Seismic Modelling and Processing
  • Extended AR Models and Applications
  • A Few Words About Nonlinear Time Series
  • Levinson's Recursion and Reflection Coefficients
  • Minimum Phase Property of the PEO
  • Information Theory and Relevant Issues
  • Introduction
  • Entropy in Time Series Analysis
  • The Kullback-Lciblcr Information Measure
  • MaxEnt and the Spectral Problem
  • The Akaike Information Criterion, AIC
  • Mutual Information and Conditional Entropy
  • The Inverse Problem
  • Introduction
  • The Linear (or Linearized) Inverse Formulation
  • Probabilistic Inversion
  • Minimum Relative Entropy Inversion
  • Bayesian Inference
  • Signal to Noise Enhancement
  • Introduction
  • f
  • x Filters
  • Principal Components, Eigenimages and the KL Transform
  • Radon Transforms
  • Time variant Radon Transforms
  • Discussion
  • Deconvolution with Applications to Seismology
  • Introduction
  • Layered Earth Model
  • Deconvolution of the Reflectivity Series
  • Sparse Deconvolution and Bayesian Analysis
  • ID Impedance Inversion
  • Nonminimum Phase Wavelet Estimation
  • Blind, Full Band Deconvolution
  • Discussion
  • A Potpourri of Some Favorite Techniques
  • Introduction
  • Physical Wavelet Frame Dcnoising
  • Stein Processing
  • The Bootstrap and the EIC
  • The Extended Information Criterion
  • Summary
  • Last Page.

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