Random Integral Equations with Applications to Life Sciences and Engineering
- 1st Edition, Volume 108 - January 1, 1974
- Editors: Chris P. Tsokos, W.J. Padgett
- Language: English
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 9 5 6 1 7 - 6
In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quote- Non-Lagrange interpolation,
- Generic Karhunen-Loeve transform
- Generalised low-rank matrix approximation
- Optimal data compression
- Optimal nonlinear filtering
Applied mathematicians and Electrical engineers
And:
Statisticians
Contents
1 Overview
I Methods of Operator Approximation in System Modelling
2 Nonlinear Operator Approximation with Preassigned Accuracy
2.1 Introduction
2.2 Generic formulation of the problem
2.3 Operator approximation in space C([0; 1]):
2.4 Operator approximation in Banach spaces by polynomial operators
2.5 Approximation on compact sets in topological vector spaces
2.6 Approximation on noncompact sets in Hilbert spaces
2.7 Special results for maps into Banach spaces
2.8 Concluding remarks
3 Interpolation of Nonlinear Operators 65
3.1 Introduction
3.2 Lagrange interpolation in Banach spaces
3.3 Weak interpolation of nonlinear operators
3.4 Some related results
3.5 Concluding remarks
4 Realistic Operators and their Approximation
4.1 Introduction
4.2 Formalization of concepts related to description of real-world objects
4.3 Approximation of R¡continuous operators
4.4 Concluding remarks
5 Methods of Best Approximation for Nonlinear Operators
5.1 Introduction
5.2 Best Approximation of nonlinear operators in Banach spaces: Deterministic case
5.3 Estimation of mean and covariance matrix for random vectors
5.4 Best Hadamard-quadratic approximation
5.5 Best polynomial approximation
5.6 Best causal approximation
5.7 Best hybrid approximations
5.8 Concluding remarks
II Optimal Estimation of Random Vectors
6 Computational Methods for Optimal Filtering of Stochastic Signals
6.1 Introduction
6.2 Optimal linear Filtering in Finite dimensional vector spaces
6.3 Optimal linear Filtering in Hilbert spaces
6.4 Optimal causal linear Filtering with piecewise constant memory
6.5 Optimal causal polynomial Filtering with arbitrarily variable memory
6.6 Optimal nonlinear Filtering with no memory constraint
6.7 Concluding remarks
7 Computational Methods for Optimal Compression and
Reconstruction of Random Data
7.1 Introduction
7.2 Standard Principal Component Analysis and Karhunen-Loeeve transform (PCA{KLT)
7.3 Rank-constrained matrix approximations
7.4 Generic PCA{KLT
7.5 Optimal hybrid transform based on Hadamard-quadratic approximation
7.6 Optimal transform formed by a combination of nonlinear operators
7.7 Optimal generalized hybrid transform
7.8 Concluding remarks
Bibliography
Index
- No. of pages: 322
- Language: English
- Edition: 1
- Volume: 108
- Published: January 1, 1974
- Imprint: Elsevier Science
- eBook ISBN: 9780080956176
CT
Chris P. Tsokos
Dr. Tsokos is the recipient of many distinguished awards and honors, including Fellow of the American Statistical Association, USF Distinguished Scholar Award, Sigma Xi Outstanding Research Award, USF Outstanding Undergraduate Teaching Award, USF Professional Excellence Award, URI Alumni Excellence Award in Science and Technology, Pi Mu Epsilon, election to the International Statistical Institute, Sigma Pi Sigma, USF Teaching Incentive Program, and several humanitarian and philanthropic recognitions and awards. He is also a member of several academic and professional societies, and serves as Honorary Editor, Chief-Editor, Editor or Associate Editor for more than twelve academic research journals. Prof. Tsokos has directed the doctoral research and been the mentor of more than 65 students.
WP