Digital and Kalman Filtering an Introduction to Discrete-Time Filtering and Optimum Linear Estimation

By:

Bozic,S. M

Material type: Text

TextOriginal language: English Publication details: Newburyport Dover Publications 2018Edition: 2Description: xi, 160 pISBN:

9780486817354 (PB)

Subject(s):

Digital Filtering

DDC classification:

BOZ 621.382

Summary: This text for advanced undergraduates and graduate students provides a concise introduction to increasingly important topics in electrical engineering: digital filtering, filter design, and applications in the form of the Kalman and Wiener filters. The first half focuses on digital filtering, covering FIR and IIR filter design and other concepts. The second half addresses filtering noisy data to extract a signal, with chapters on nonrecursive (FIR Wiener) estimation, recursive (Kalman) estimation, and optimum estimation of vector signals. The treatment is presented in tutorial form, but readers are assumed to be familiar with basic circuit theory, statistical averages, and elementary matrices. Central topics are developed gradually, including both worked examples and problems with solutions, and this second edition features new material and problems

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	IIITDM Kurnool	Non-fiction	621.382 BOZ (Browse shelf(Opens below))	Available		0005396

This text for advanced undergraduates and graduate students provides a concise introduction to increasingly important topics in electrical engineering: digital filtering, filter design, and applications in the form of the Kalman and Wiener filters. The first half focuses on digital filtering, covering FIR and IIR filter design and other concepts. The second half addresses filtering noisy data to extract a signal, with chapters on nonrecursive (FIR Wiener) estimation, recursive (Kalman) estimation, and optimum estimation of vector signals.
The treatment is presented in tutorial form, but readers are assumed to be familiar with basic circuit theory, statistical averages, and elementary matrices. Central topics are developed gradually, including both worked examples and problems with solutions, and this second edition features new material and problems

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