Muutke küpsiste eelistusi

Mathematical Methods in Time Series Analysis and Digital Image Processing 2008 ed. [Kõva köide]

Edited by , Edited by , Edited by , Edited by
  • Formaat: Hardback, 294 pages, kõrgus x laius: 235x155 mm, kaal: 686 g, 13 Illustrations, color; 96 Illustrations, black and white; XIV, 294 p. 109 illus., 13 illus. in color., 1 Hardback
  • Sari: Understanding Complex Systems
  • Ilmumisaeg: 10-Jan-2008
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540756310
  • ISBN-13: 9783540756316
  • Kõva köide
  • Hind: 95,02 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 111,79 €
  • Säästad 15%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
  • Formaat: Hardback, 294 pages, kõrgus x laius: 235x155 mm, kaal: 686 g, 13 Illustrations, color; 96 Illustrations, black and white; XIV, 294 p. 109 illus., 13 illus. in color., 1 Hardback
  • Sari: Understanding Complex Systems
  • Ilmumisaeg: 10-Jan-2008
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540756310
  • ISBN-13: 9783540756316
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences.



In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/environmental sciences, is also addressed.



This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.
Multivariate Time Series Analysis.- Surrogate Data A Qualitative and
Quantitative Analysis.- Multiscale Approximation.- Inverse Problems and
Parameter Identification in Image Processing.- Analysis of Bivariate Coupling
by Means of Recurrence.- Structural Adaptive Smoothing Procedures.- Nonlinear
Analysis of Multi-Dimensional Signals: Local Adaptive Estimation of Complex
Motion and Orientation Patterns.