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Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements [Mīkstie vāki]

  • Formāts: Paperback / softback, 256 pages, height x width x depth: 228x152x12 mm, weight: 350 g
  • Izdošanas datums: 28-Jun-2019
  • Izdevniecība: Dover Publications Inc.
  • ISBN-10: 0486832988
  • ISBN-13: 9780486832982
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  • Formāts: Paperback / softback, 256 pages, height x width x depth: 228x152x12 mm, weight: 350 g
  • Izdošanas datums: 28-Jun-2019
  • Izdevniecība: Dover Publications Inc.
  • ISBN-10: 0486832988
  • ISBN-13: 9780486832982
Citas grāmatas par šo tēmu:
In this graduate-level monograph, S. Twomey, a professor of atmospheric sciences, develops the background and fundamental theory of inversion processes used in remote sensing — e.g., atmospheric temperature structure measurements from satellites—starting at an elementary level.
The text opens with examples of inversion problems from a variety of disciplines, showing that the same problem—solution of a Fredholm linear integral equation of the first kind — is involved in every instance. A discussion of the reduction of such integral equations to a system of linear algebraic equations follows. Subsequent chapters examine methods for obtaining stable solutions at the expense of introducing constraints in the solution, the derivation of other inversion procedures, and the detailed analysis of the information content of indirect measurements. Each chapter begins with a discussion that outlines problems and questions to be covered, and a helpful Appendix includes suggestions for further reading.


Graduate-level monograph develops background and fundamental theory of inversion processes used in remote sensing — e.g., atmospheric temperature structure measurements from satellites — starting at elementary level. Largely self-contained. 1977 edition.
List of frequently used symbols and their meanings
vii
Preface ix
Chapter 1 Introduction
1(26)
1.1 Mathematical description of the response of a real physical remote sensing system
3(6)
1.2 Examples of real inversion problems
9(15)
Bibliography
24(3)
Chapter 2 Simple Problems Involving Inversion
27(10)
2.1 Algebraic elimination
28(5)
2.2 Quadrature, the reduction of integral equations to systems of linear equations
33(3)
Bibliography
36(1)
Chapter 3 Theory of Large Linear Systems
37(16)
3.1 Matrix-vector algebra
37(3)
3.2 Matrix products
40(2)
3.3 Inverse of a matrix
42(6)
3.4 Transposition and rules for product inversion
48(4)
Bibliography
52(1)
Chapter 4 Physical and Geometric Aspects of Vectors and Matrices
53(30)
4.1 Geometric vectors
53(6)
4.2 Norms, length and distance
59(1)
4.3 Orthogonality
60(3)
4.4 Geometrical view of matrix operations
63(4)
4.5 Eigenvalues and eigenvectors
67(9)
4.6 Quadratic forms, eigenvalues and eigenvectors
76(5)
Bibliography
81(2)
Chapter 5 Algebraic and Geometric Aspects of Functions and Function Space
83(32)
5.1 Orthogonality, norms and length
84(6)
5.2 Other kinds of orthogonality
90(5)
5.3 Approximation by sums of functions
95(5)
5.4 Integral equations
100(5)
5.5 The Fourier transform and Fourier series
105(8)
5.6 Spectral form of the fundamental integral equation of inversion
111(2)
Bibliography
113(2)
Chapter 6 Linear Inversion Methods
115(36)
6.1 Quadrature inversion
115(5)
6.2 Least squares solution
120(2)
6.3 Constrained linear inversion
122(5)
6.4 Sample applications of constrained linear inversion
127(17)
6.5 Algebraic nature of constrained linear inversion
144(2)
6.6 Geometric nature of constrained linear inversion
146(3)
Bibliography
149(2)
Chapter 7 Further Inversion Techniques
151(34)
7.1 More elaborate treatments of error components in linear inversions
152(6)
7.2 The synthesis approach to inversion
158(11)
7.3 Solution in terms of kernels
169(3)
7.4 The Prony algorithm --- a non-linear inversion method
172(4)
7.5 Landweber iteration
176(3)
7.6 Iterative, non-linear methods of inversion
179(5)
Bibliography
184(1)
Chapter 8 Information Content of Indirect Sensing Measurements
185(28)
8.1 How many measurements?
185(2)
8.2 Interdependence of kernels
187(2)
8.3 Extrema of quadratic forms
189(2)
8.4 Application to the interdependence problem for the kernels
191(8)
8.5 Information content
199(3)
8.6 Independence analysis applied to measured quantities
202(5)
8.7 Error magnification
207(5)
Bibliography
212(1)
Chapter 9 Further Topics
213(18)
9.1 Further examples of inversions and their behavior
214(5)
9.2 Beneficial aspects of kernel interdependence
219(5)
9.3 Inference of more unknowns than there are measurements
224(1)
9.4 Inversions in which the unknown is a matrix
225(1)
9.5 Prediction and inversion
226(5)
APPENDIX
231(4)
1 Determinants
231(1)
2 Matrix properties involving determinants
232(2)
3 Solution by determinants of a linear system of equations
234(1)
Suggestions for further reading 235(4)
Name Index 239(2)
Subject index 241