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Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB
book

Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

by Robert Duin, Ferdinand van der Heijden, Dick de Ridder, David M. J. Tax
November 2004
Intermediate to advanced
440 pages
10h 52m
English
Wiley
Content preview from Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB

Appendix A

Topics Selected from Functional Analysis

This appendix summarizes some concepts from functional analysis. The concepts are part of the mathematical background required for understanding this book. Mathematical peculiarities not relevant in this context are omitted. Instead, at the end of the appendix references to more detailed treatments are given.

A.1 LINEAR SPACES

A linear space (or vector space) over a field F is a set R with elements (vectors) f, g, h, … equipped with two operations:

  • images
  • scalar multiplication (αf with α ∈ F): F × R → R

Usually, the field F is the set images of real numbers, or the set images of complex numbers. The addition and the multiplication operation must satisfy the following axioms:

  • (a) f + g = g + f
  • (b) (f + g) + h = f + (g + h)
  • (c) a so-called zero element 0 ∈ R exists such that f + 0 = f
  • (d) a negative element −f exists for each f such that f + ( −f) = 0
  • (e) α(f + g) = αf + αg
  • (f) (α + β)f = αf + βf
  • (g) (αβ)f = α(β)f
  • (h) 1f = f

A linear subspace S of a linear space R is a subset of R which itself is linear. A condition sufficient and necessary for a subset S ⊂ R to be linear is that αf + βg ∈ S for all f, g ∈ S and for all α, β ∈ F.

Examples

is the ...

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Publisher Resources

ISBN: 9780470090138Purchase book