First Advisor

Y.C. Jenq

Date of Publication

1-14-1994

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Electrical Engineering

Department

Electrical Engineering

Language

English

Subjects

Algorithms, Adaptive filters

DOI

10.15760/etd.6686

Physical Description

1 online resource (iv, 59 p.)

Abstract

The thesis presents a new adaptive notch filter (ANF) algorithm that is more accurate and efficient and has a faster convergent rate than previous ANF algorithms. In 1985, Nehorai designed an infinite impulse response (UR) ANF algorithm that has many advantages over previous ANF algorithms. It requires a minimal number of parameters with constrained poles and zeros. It has higher stability and sharper notches than any ANF algorithm until now. Because of the special filter structure and the recursive prediction error (RPE) method, however, the algorithm is very sensitive to the initial estimate of the filter coefficient and its covariance. Furthermore, convergence to the true filter coefficient is not guaranteed since the error-performance surface of the filter has its global minimum lying on a fairly flat region. We propose a new ANF algorithm that overcomes the convergence problem. By choosing a smaller notch bandwidth control parameter that makes the error-performance surface less flat, we can more easily detect a global minimum. We also propose a new convergence criterion to be used with the algorithm and a self-adjustment feature to reset the initial estimate of the filter coefficient and its covariance. This results in guaranteed convergence with more accurate results and more efficient computations than previous ANF algorithms.

Rights

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Comments

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Persistent Identifier

https://archives.pdx.edu/ds/psu/28006

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