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Linear Estimation and Detection in Krylov Subspaces [electronic resource] / by Guido K.E. Dietl.

By: Dietl, Guido K.E [author.]Contributor(s): SpringerLink (Online service)Material type: Text

TextLanguage: English Series: Foundations in Signal Processing, Communications and Networking: 1Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Description: XIX, 232 p. 53 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540684794Subject(s): Engineering | Computer science | Statistics | Engineering mathematics | Engineering | Signal, Image and Speech Processing | Computational Science and Engineering | Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences | Math Applications in Computer Science | Appl.Mathematics/Computational Methods of EngineeringAdditional physical formats: Printed edition:: No titleDDC classification: 621.382 LOC classification: TK5102.9TA1637-1638TK7882.S65Online resources: Click here to access online

Contents:

Theory: Linear Estimation in Krylov Subspaces -- Efficient Matrix Wiener Filter Implementations -- Block Krylov Methods -- Reduced-Rank Matrix Wiener Filters in Krylov Subspaces -- Application: Iterative Multiuser Detection -- System Model for Iterative Multiuser Detection -- System Performance -- Conclusions.

In: Springer eBooksSummary: This book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems. The investigations include -exact computational complexity considerations and - performance analysis based on extrinsic information transfer charts as well as Monte-Carlo simulations.

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This book focuses on the foundations of linear estimation theory which is essential for effective signal processing. In its first part, it gives a comprehensive overview of several key methods like reduced-rank signal processing and Krylov subspace methods of numerical mathematics. Based on the derivation of the multistage Wiener filter in its most general form, the relationship between statistical signal processing and numerical mathematics is presented. In the second part, the theory is applied to iterative multiuser detection receivers (Turbo equalization) which are typically desired in wireless communication systems. The investigations include -exact computational complexity considerations and - performance analysis based on extrinsic information transfer charts as well as Monte-Carlo simulations.

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