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Performance Analysis and Applications of Optimal Linear Smoothing Prediction

This thesis focuses on the design and analysis of an optimal filter that is capable of making one-step-ahead prediction of a bandlimited signal while attenuating unwanted noise. First, the filter optimization based on the least mean-square-error criterion is presented. Then, an exact expression for the achievable minimum mean square error (MMSE) is derived with the aid of the Toeplitz form method and Szego theory. Based on this MMSE expression, the formulae for estimating the optimal filter¡¦s in-band prediction error and out-of-band noise attenuation are derived. Finally, the optimal filter is applied to sigma-delta modulation. It shows that the modulation performance and stability are intimately related to the filter performance and can be accurately estimated by the derived formulae.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0907110-145815
Date07 September 2010
CreatorsChen, Chia-Wei
ContributorsChung-Yao Kao, Tsang-Yi Wang, Chih-Chiang Cheng, Shiang-Hwua Yu
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0907110-145815
Rightsunrestricted, Copyright information available at source archive

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