© 1990

Linear Prediction Theory

A Mathematical Basis for Adaptive Systems


Part of the Springer Series in Information Sciences book series (SSINF, volume 21)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Peter Strobach
    Pages 1-12
  3. Peter Strobach
    Pages 13-36
  4. Peter Strobach
    Pages 102-157
  5. Peter Strobach
    Pages 158-196
  6. Peter Strobach
    Pages 197-233
  7. Peter Strobach
    Pages 234-280
  8. Peter Strobach
    Pages 281-311
  9. Peter Strobach
    Pages 312-335
  10. Peter Strobach
    Pages 336-340
  11. Back Matter
    Pages 341-422

About this book


Lnear prediction theory and the related algorithms have matured to the point where they now form an integral part of many real-world adaptive systems. When it is necessary to extract information from a random process, we are frequently faced with the problem of analyzing and solving special systems of linear equations. In the general case these systems are overdetermined and may be characterized by additional properties, such as update and shift-invariance properties. Usually, one employs exact or approximate least-squares methods to solve the resulting class of linear equations. Mainly during the last decade, researchers in various fields have contributed techniques and nomenclature for this type of least-squares problem. This body of methods now constitutes what we call the theory of linear prediction. The immense interest that it has aroused clearly emerges from recent advances in processor technology, which provide the means to implement linear prediction algorithms, and to operate them in real time. The practical effect is the occurrence of a new class of high-performance adaptive systems for control, communications and system identification applications. This monograph presumes a background in discrete-time digital signal processing, including Z-transforms, and a basic knowledge of discrete-time random processes. One of the difficulties I have en­ countered while writing this book is that many engineers and computer scientists lack knowledge of fundamental mathematics and geometry.


Signal Signal Processing algorithm algorithms communication computer science control systems geophysics system system identification

Authors and affiliations

  1. 1.ZFE IS — Forschung für Informatik und SoftwareSIEMENS AG, Zentralabteilung Forschung und EntwicklungMünchen 83Fed. Rep. of Germany

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