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picture1_Lecture Ppt 81181 | Gdalec14


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File: Lecture Ppt 81181 | Gdalec14
syllabus lecture 01 describing inverse problems lecture 02 probability and measurement error part 1 lecture 03 probability and measurement error part 2 lecture 04 the l norm and simple least ...

icon picture PPTX Filetype Power Point PPTX | Posted on 08 Sep 2022 | 3 years ago
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                                           Syllabus
   Lecture 01      Describing Inverse Problems
   Lecture 02      Probability and Measurement Error, Part 1
   Lecture 03      Probability and Measurement Error, Part 2 
   Lecture 04      The L  Norm and Simple Least Squares
                        2
   Lecture 05      A Priori Information and Weighted Least Squared
   Lecture 06      Resolution and Generalized Inverses
   Lecture 07      Backus-Gilbert Inverse and the Trade Off of Resolution and Variance
   Lecture 08      The Principle of Maximum Likelihood
   Lecture 09      Inexact Theories
   Lecture 10      Nonuniqueness and Localized Averages
   Lecture 11      Vector Spaces and Singular Value Decomposition
   Lecture 12      Equality and Inequality Constraints
   Lecture 13      L , L  Norm Problems and Linear Programming
                    1   ∞
   Lecture 14      Nonlinear Problems: Grid and Monte Carlo Searches 
   Lecture 15      Nonlinear Problems: Newton’s Method 
   Lecture 16      Nonlinear Problems:  Simulated Annealing and Bootstrap Confidence Intervals 
   Lecture 17      Factor Analysis
   Lecture 18      Varimax Factors, Empircal Orthogonal Functions
   Lecture 19      Backus-Gilbert Theory for Continuous Problems; Radon’s Problem
   Lecture 20      Linear Operators and Their Adjoints
   Lecture 21      Fréchet Derivatives
   Lecture 22      Exemplary Inverse Problems, incl. Filter Design
   Lecture 23      Exemplary Inverse Problems, incl. Earthquake Location
   Lecture 24      Exemplary Inverse Problems, incl. Vibrational Problems
      Purpose of the Lecture
   Discuss two important issues related to probability
      Introduce linearizing transformations
       Introduce the Grid Search Method
      Introduce the Monte Carlo Method
          Part 1
     two issue related to probability
    not limited to nonlinear problems
          but
     they tend to arise there a lot
       issue #1
   distribution of the data matters
                          d(z) vs. z(d)
                    d(z)                z(d)               d(z)
              6                   6                   6
              5                   5                   5
              4                   4                   4
             d3                  z3                  d3
              2                   2                   2
              1                   1                   1
              00    2    4    6   00    2    4    6   00    2    4    6
                      z                   d                   z
              not quite the same
              intercept -0.500000 slope 1.300000
              intercept -0.615385 slope 1.346154
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...Syllabus lecture describing inverse problems probability and measurement error part the l norm simple least squares a priori information weighted squared resolution generalized inverses backus gilbert trade off of variance principle maximum likelihood inexact theories nonuniqueness localized averages vector spaces singular value decomposition equality inequality constraints linear programming nonlinear grid monte carlo searches newton s method simulated annealing bootstrap confidence intervals factor analysis varimax factors empircal orthogonal functions theory for continuous radon problem operators their adjoints frechet derivatives exemplary incl filter design earthquake location vibrational purpose discuss two important issues related to introduce linearizing transformations search issue not limited but they tend arise there lot distribution data matters d z vs quite same intercept slope...

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