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Classification, Parameter Estimation and State Estimation, 2nd Edition
book

Classification, Parameter Estimation and State Estimation, 2nd Edition

by Bangjun Lei, Guangzhu Xu, Ming Feng, Yaobin Zou, Ferdinand van der Heijden, Dick de Ridder, David M. J. Tax
May 2017
Beginner to intermediate
480 pages
11h 17m
English
Wiley
Content preview from Classification, Parameter Estimation and State Estimation, 2nd Edition

ATopics 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:

  • Addition (f + g): R × R → R
  • Scalar multiplication (αf with α ∈ F): F × R → R

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

  1. f + g = g + f
  2. (f + g) + h = f + (g + h)
  3. a so-called zero element 0 ∈ R exists such that f + 0 = f
  4. a negative element − f exists for each f such that f + ( − f) = 0
  5. α(f + g) = αf + αg
  6. (α + β)f = αf + βf
  7. (αβ)f = α(βf)
  8. 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 set of ...

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Publisher Resources

ISBN: 9781119152439Purchase book