DOCSLIB.ORG

One-Dimensional Processing for Adaptive Image Restoration

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
One-Dimensional Processing for Adaptive Image Restoration DOCUMENT OFFICE 36-412 JRESEARCH LABORATORY OF ELECTRONtCS *l MASSACHUSETTS INSTITUTE OF TECHNOLOGY ~~~~~~~~~IllLf llii One-Dimensional Processing for Adaptive Image Restoration Philip Chan tl 1; 4 eo'p ON// Technical Report 501 June 1984 Massachusetts Institute of Technology Research Laboratory of Electronics Cambridge, Massachusetts 02139 _ ___I __ _ __ __I_L *1 One-Dimensional Processing for Adaptive Image Restoration Philip Chan Technical Report 501 June 1984 Massachusetts Institute of Technology Research Laboratory of Electronics Cambridge, Massachusetts 02139 This work has been supported in part by the Advanced Research Projects Agency monitored by ONR under Contract N00014-81-K-0742 NR-049-506 and in part by the National Science Foundation under Grant ECS80-07102. _ __YLII··_I__IIL____yll_·ll-... -____. -- 1~ - - -- 1-~· 1 --- I I - ---·---- -- - _I __I __I UNCLASSIFTED SECUNITY CLASSIFICATION OF rIS PAGE REPORT OOCUMENTATION PAGE l& RPICORT SECURITY CLASSFPlCATION 1I RISTRlCTIVI MARKINGS 2& SICURITY C1ASSIFICATION AUTHORITY 3. OISTrIUUTIONIAVAILA6I1UTY OF RIPORT Approved for public release: distribution =6 O0CLAIf CATNoOWNGrAOlING sc.eout.a unlimited A. PRAFORMING ORGANIZATION IrEPoRTHMUSll(S) S. MONITORING ORGANIZATION REPORT NUM6EE(S) G. NAMIE OF PRFORlOMING ORGcANIZATION . OFICI( SYMKOL 7 NAM_ OF MONITORING ORGANIZATION Research Laboratory of Elec to mehe, Office of Naval Research Massachusetts Institute of Te:hnology Mathematical and Information Scien. Div. 6. A^OORSS (Ct. Saw emd ZIP Code) 7b. AOORESS =Ct. 31w .nJi ZIP Come 77 Massachusetts Avenue 800 North Quincy Street Cambridge, MA 02139 Arlington, Virginia 22217 &L NAM OF IINOIN(OWSPONSORING a OFICE SYMh t.oL L Ps1OCUtEMENT INSTRUMENT OENTIltCATION NUMllR ORGANIZATION (If WIawieal Advanced Research Projects .gency N00014-8 1-K-0742 Se. A0OOR1S (City. State M ZIP CoMg IC. SOURC OF FUNOING NMOe 1400 Wilson Boulevard PROGRAM PROJcr TASK WORK UNIT Arlington, Virginia 22217 UAMNT N4. NO. NO. NO. ,. 1TL. aclm i,y ,,C clo,, One-neDimens i on.al 049 - 506 Processina for AdaPtive Imace Restoration" unclassified 12. P1O13NAL AUTWOR4)1 C..an . ph; I iI n t3.. TYPE oF RSPORT 13b rtIME COVERSO 14. OATrs OF RePORT Yr.. ... Qe7 15. PAGE COUNT Technical PRO" rO 1984 June 100 i1. SUFPL9.MNTARY NOTATION Technical Report No. 501 17. COSAct COOS, _ 1i . SUlJCr TRMS Cmauae on eem'e ifeewesn seamide4mty be bbme nub " PItO0 GPROUP I sue GR. 19. A6TtRACT Cotiurw o vW if MOmeesww se imdfy by btai rnubet A one-dimensional (1-0) approach to the problem of adaptive image restoration is pre- sented. n this approach, we use a cascade of four L-O adaptive filters oriented in the four major correlation directions of the image, with each filter treating the image as a 1-0 signal. The objective of this L-0 approach is to improve the performance of the more general two-dimensional (2-0) approach. This differs considerably from previous L-0 approaches, he objectives of which have typically been to approximate a more general 2-0 approach for computational reasons and not to improve its performance. The main advan- tage of this new 1-0 approach is its capability to preserve edges in the image while removing noise in all regions of the image, including the edge regions. To illustrate this point, the approach is applied to existing 2-0 image restoration algorithms. Exper- Lmental results with images degraded by additive white noise at various SNRs (signal-to- noise ratios) are oprsented. Further examples illustrate the application of -0 rstor- ation techniques based on this approach to images degraded by blurring and additive white noise and images degraded by multiplicative noise. Another example shows ts use- fulness in the reduction of quantization noise in pulse code modulation image coding. 20. 01STRIBUTIONAVAILABI .ITY OF ABSTRACT 21. ASSTRACt SECURITY CZ.ASIIC ATION UNCLASSI.S eOIUNLIMITO SAMe S a. '-- OgTC U.iS * Unclassified 22& NME1 OF RESPONSiBLE INOIVIOAI 2 ELEPONE NUM6ER 22c. OFFICESYrMBOLA Kyra M. Hall (Ineid Am Ca"e P e T nTrt (617) 53-2569 .~ _ -L LJU rJ1liV 14/ , 4 A'R 501ON OF JAN 73 s Q50SOL.ETS. 1 UNCLASS IFZT' SECURITY C.ASSIFICAITON OF THS PAGa _X_____I_11____11-·I^I·_ULY·I·sYS..-. 111_1_1_11_111____·_ __1 I- _· __ __ -2- ONE-DIMENSIONAL PROCESSING FOR ADAPTIVE IMAGE RESTORATION by Philip Chan Submitted to the Department of Electrical Engineering and Computer Science, on May 11, 1984, in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering and Computer Science. ABSTRACr A one-dimensional (1-D) approach to the problem of adaptive image res- toration is presented. In this approach, we use a cascade of four 1-D adaptive filters oriented in the four major correlation directions of the image, with each filter treating the image as a 1-D signal. The objective of this 1-D approach is to improve the performance of the more general two-dimensional (2-D) approach. This differs considerably from previous 1-D approaches, the objectives of which have typically been to approximate a more general 2-D approach for computa- tional reasons and not to improve its performance. The main advantage of this new 1-D approach is its capability to preserve' edges in the image while remov- ing noise in all regions of the image, including the edge regions. To illustrate this point, the approach is applied to existing 2-D image restoration algorithms. Experimental results with images degraded by additive white noise at various SNRs (signal to noise ratios) are presented. Further examples illustrate the application of 1-D restoration techniques based on this approach to images degraded by blurring and additive white noise and images degraded by multipli- cative noise. Another example shows its usefulness in the reduction of quanti- zation noise in pulse code modulation image coding. Thesis Supervisor: Professor Jae S. Lim Title: Associate Professor of Electrical Engineering 111111···1(··111-Llltll_. ..-1Il-LII- -_I_ __ I __ I _ -3- ACKNOWLEDGEMENTS My deepest appreciation goes to Professor Jae S. Lim for his supervi- sion of this thesis. His encouragement, understanding, and patience have made my graduate study at MIT a very fruitful and enjoyable one. I would like to thank all members of the Digital Signal Processing Group at MIT who provided an excellent research environment. Special thank goes to members of the Cognitive Information Processing Group at MIT who assisted me in producing hard copies of the images in this thesis on their facili- ties. I am deeply indebted to my parents whose care and teaching have played an important role in the success of my study. Special thanks are due to my wife, Ai Hwa. Her loving care and encouragement have supported me throughout my stay at MIT. She has also helped in the preparation of this document. Finally, I gratefully acknowledge the financial support by the Govern- ment of Singapore whose DSO Scholarship has supported my graduate educa- tion. ___III·_____ILIY___111· 11 1_11_111_1-.__-·-·-LII-SP---^l---X-l-·-- I--· _I------ I -4- TABLE OF CONTENTS ABSTRACT 2 ACKNOWLEDGEIMENTS 3 TABLE OF CONTENTS 4 LIST OF FIGURES 7 LIST OF TABLES 12 CHAPTER 1 INTRODUCTION 13 Introduction 13 12 Scope of the Thesis 16 13 Organization of Chapters 18 CHAPTER 2: REVIEW OF IMAGE RESTORATION 20 21 Introduction 20 22 Representations of Images and Degradations 21 23 Nonadaptive Image Restoration 26 2.4 Adaptive Image Restoration 29 25 One-Dimensional Approximations to Two-dimensional Image Restoration 31 2.6 Summary 35 CHAPTER 3: A ONE-DIMENSIONAL APPROACH TO ADAPTIVE IMAGE RESTORATION 36 3.1 Introduction 36 32 Motivation of the Approach 37 33 The Basic Principle 38 3A Discussion 40 3A.4. Advantages of the Approach 40 _ ^I1_1II1_I______XYIl·llll·llillpl·I(IQ. 11141^. 111·1 II -~~~ ~I -5- 3.42 Comparison with Other 1-D Approaches 41 3.43 Practical Considerations 43 35 Conclusion 44 CHAPTER 4: APPLICATIONS OF THE ONE-DIMENSIONAL APPROACH 45 4.1 Introduction 45 42 Adaptive Filter Based on Local Statistics 46 421 The 2-D LLSE Algorithm 46 422 The 1-D LLSE Algorithm 49 423 Experimental Results 50 43 Adaptive Filter Based on a Noise Visibility Function 59 431 The 2-D S-type Filter 59 432 The -IDS-type Filter 63 433 Experimental Results 63 4A Short Space Spectral Subtraction Technique 65 4.41 The 2-D Short Space Spectral Subtraction Technique 65 4A2 The 1-D Short Space Spectral Subtraction Technique 67 4A43 Experimental Results 69 45 Summary and Conclusion 70 CHA PTER 5: FURTHER APPLICATIONS OF THE ONE-DIMENSIONAL APPROACH 73 51 Introduction 73 52 Restoration of Blurred and Noisy Images 74 521 The Principle of Inverse Filtering 74 522 Experimental Results 76 53 Restoration of Images Degraded by Multiplicative Noise 76 -6- 531 Filtering of Speckle Degraded Images in the Density Domain 79 532 Experimental Results 80 5.4 An Application to Noise Reduction in Image Coding 84 5.41 A Quantization Noise Reduction Scheme 84 542 Experimental Results 86 55 Conclusion 91 CHAPTER 6: SUMMARY AND CONCLUSION 93 61 Summary 93 62 Suggestions for Future Work 95 63 Conclusion 96 REFERENCES 97 _I_____·IIIYIUULI_- _III-----·- ^ ·-----I_·I · I--- _ ·__ I -7- LIST OF FIGURES Figure 31 (a) A 2-D restoration method. 39 (b) The proposed 1-D approach. Figure 32 General block diagram of other 1-D approaches. 42 Figuree41 General block diagram of a restoration technique 48 based on local statistics. Figure: 42 (a) Original image. 51 (b) Noisy image. (c) Image in (b) restored by the 2-D LLSE algorithm. Figure 43 (a) Figure 42(b) processed by the horizontal filter. 52 (b) Image in (a) processed by the vertical filter. (c) Image in (b) processed by the 45-degree filter. (d) Image in (c) processed by the 135-degree filter.
Load more

Recommended publications
  • Lossless Audio Coding Using Adaptive Linear Prediction
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by ScholarBank@NUS LOSSLESS AUDIO CODING USING ADAPTIVE LINEAR PREDICTION SU XIN RONG (B.Eng., SJTU, PRC) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2005 ACKNOWLEDGEMENTS First of all, I would like to take this opportunity to express my deepest gratitude to my supervisor Dr. Huang Dong Yan from Institute for Infocomm Research for her continuous guidance and help, without which this thesis would not have been possible. I would also like to specially thank my supervisor Assistant Professor Nallanathan Arumugam from NUS for his continuous support and help. Finally, I would like to thank all the people who might help me during the project. ii TABLE OF CONTENTS ACKNOWLEDGEMENTS .............................................................................................. ii TABLE OF CONTENTS ................................................................................................. iii SUMMARY ........................................................................................................................vi LIST OF TABLES .......................................................................................................... viii LIST OF FIGURES ...........................................................................................................ix CHAPTER 1 INTRODUCTION.........................................................................................................
    [Show full text]
  • Total Harmonics Distortion Reduction Using Adaptive, Weiner, and Kalman Filters
    Western Michigan University ScholarWorks at WMU Master's Theses Graduate College 6-2016 Total Harmonics Distortion Reduction Using Adaptive, Weiner, and Kalman Filters Liqaa Alhafadhi Follow this and additional works at: https://scholarworks.wmich.edu/masters_theses Part of the Electrical and Computer Engineering Commons Recommended Citation Alhafadhi, Liqaa, "Total Harmonics Distortion Reduction Using Adaptive, Weiner, and Kalman Filters" (2016). Master's Theses. 737. https://scholarworks.wmich.edu/masters_theses/737 This Masters Thesis-Open Access is brought to you for free and open access by the Graduate College at ScholarWorks at WMU. It has been accepted for inclusion in Master's Theses by an authorized administrator of ScholarWorks at WMU. For more information, please contact [email protected]. TOTAL HARMONICS DISTORTION REDUCTION USING ADAPTIVE, WEINER, AND KALMAN FILTERS by Liqaa Alhafadhi A thesis submitted to the Graduate College in partial fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical) Electrical and Computer Engineering Western Michigan University June 2016 Thesis Committee: Johnson Asumadu, Ph.D., Chair Massood Atashbar, Ph.D. Christopher Cho, Ph.D. TOTAL HARMONICS DISTORTION REDUCTION USING ADAPTIVE, WEINER, AND KALMAN FILTERS Liqaa Alhafadhi, M.S.E. Western Michigan University, 2016 Total harmonics distortion is one of the main problems in power systems due to its effects in generating undesirable issues in power quality. These effects include heating (in transformers, capacitors, motors, and generators), disoperation of electronic equipment, incorrect readings on meters, disoperation of protective relays, and communication interference. Besides these problems, harmonics affect the power quality in both transmission and distribution systems. Different techniques have been used to mitigate the effects of harmonics.
    [Show full text]
  • Adaptive Filtering and Change Detection Fredrik Gustafsson Copyright © 2000 John Wiley & Sons, Ltd Isbns: 0-471-49287-6 (Hardback); 0-470-84161-3 (Electronic)
    Adaptive Filtering and Change Detection Fredrik Gustafsson Copyright © 2000 John Wiley & Sons, Ltd ISBNs: 0-471-49287-6 (Hardback); 0-470-84161-3 (Electronic) Adaptive Filtering and Change Detection Adaptive Filtering and Change Detection Fredrik Gustafsson Linkoping University, Linkoping, Sweden JOHN WILEY & SONS, LTD Chichester Weinheim NewYork Brisbane Singapore Toronto Copyright 0 2000 by John Wiley & Sons Ltd Baffins Lane, Chichester, West Sussex, PO 19lUD, England National 01243 779777 International (+44) 1243 779777 e-mail (for orders and customer service enquiries): [email protected] Visit our Home Page on http://www.wiley.co.uk or http://www.wiley.com All Rights Reserved.No part of this publication may be reproduced, storedin a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the termsof the Copyright Designs and PatentsAct 1988 or under the termsof a licence issuedby the Copyright Licensing Agency,90 Tottenham Court Road, London, W1P 9HE,UK, without the permissionin writing of the Publisher, with the exceptionof any material supplied specifically for the purposeof being entered and executed on a computer system, for exclusive use by the ofpurchaser the publication. Neither the authors nor John Wiley& Sons Ltd accept any responsibility or liability for loss or damage occasioned to any person or property through using the material, instructions, methods or ideas contained herein, or acting or refraining from actingas a result of such use. The authors and Publisher expressly disclaim all implied warranties, including merchantabilityof fitness for any particular purpose. There will be no duty on the authorsof Publisher to correct any errorsor defects in the software.
    [Show full text]
  • Adaptive Filtering and Artificial Intelligence Methods on Fetal Ecg Extraction
    Journal of Critical Reviews ISSN- 2394-5125 Vol 7, Issue 7, 2020 ADAPTIVE FILTERING AND ARTIFICIAL INTELLIGENCE METHODS ON FETAL ECG EXTRACTION Dr. M. Pradeepa1,Dr. S. Kumaraperumal2 1Assistant Professor (Sr.), School of Information Technology, Vellore Institute of Technology, Vellore, India. Email: [email protected] 2Sr. Assistant Professor , Xavier Institute of Management & Entrepreneurship, Bangalore, India. Email: [email protected] Corresponding Author Email ID [email protected] Received: 11.02.2020 Revised: 19.03.2020 Accepted: 23.04.2020 Abstract Above 30 percent of infant’s death occur due to heart problem like congenital heart disease during 2004 in United States of America. Every year, one in 125 infants is born with heart imperfection. To address these problems, early identification of cardiac anomalies and consistent monitoring of fetal heart can support Pediatric Cardiologist and Obstetrics to take necessary care on time to prescribe medicines and take precautionary measures during gestation period, delivery and/or after birth. Majority of cardiac abnormalities contain some symptoms in the cardiac electrical signal morphology. Electrocardiography gives more information in measuring cardiac signals compare to sonographic measurement. However, in non-invasive heartbeat recording by fetal Electrocardiogram (ECG) application Electrocardiography has its limitation due to low signal- noise ratio where impeding bio-signals are too stronger than fetal electrocardiogram signals. Various adaptive filtering and Artificial intelligence techniques are applied to solve this complex problem. The complex real world problems need a combination of knowledge, skills, and techniques from various sources as an intelligent system. That intelligent system should possess expertise of human, adjust itself to changing environment and learn to improve on its own.
    [Show full text]
  • Image Restoration with Two-Dimensional Adaptive Filter
    Image Denoising with Two-Dimensional Adaptive Filter Algorithms M. Shams Esfand Abadi* and S. Nikbakht* Abstract: Two-dimensional (2D) adaptive filtering is a technique that can be applied to many image and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to 2D structure and the novel 2D adaptive filters are established. Based on this extension, the 2D variable step-size normalized least mean squares (2D-VSS- NLMS), the 2D-VSS affine projection algorithms (2D-VSS-APA), the 2D set-membership NLMS (2D-SM-NLMS), the 2D-SM-APA, the 2D selective partial update NLMS (2D- SPU-NLMS), and the 2D-SPU-APA are presented. In 2D-VSS adaptive filters, the step- size changes during the adaptation which leads to improve the performance of the algorithms. In 2D-SM adaptive filter algorithms, the filter coefficients are not updated at each iteration. Therefore, the computational complexity is reduced. In 2D-SPU adaptive algorithms, the filter coefficients are partially updated which reduce the computational complexity. We demonstrate the good performance of the proposed algorithms thorough several simulation results in 2D adaptive noise cancellation (2D-ANC) for image denoising. The results are compared with the classical 2D adaptive filters such as 2D-LMS, 2D-NLMS, and 2D-APA. Keywords: Two Dimensional, Adaptive Filter, Noise Cancellation, Selective Partial Update, Variable Step-Size, Set-Membership. 1 Introduction` one direction, was proposed in [7]. Also, the Adaptive filter algorithms have numerous applications development of a 2D adaptive filter using the block in electrical engineering [1], [2] and [3]. Two- diagonal LMS method was presented in [8].
    [Show full text]
  • Determination of Optimum Step Size of LMS Algorithm in De-Noising of Image
    Determination of Optimum Step Size of LMS Algorithm in De-noising of Image This Major project in partial fulfillment for the award of the degree of Bachelor of Science In Information and Communication Engineering Department of ECE, Faculty of Science and Engineering East West University, Dhaka Bangladesh Developed By Sharmin Akter Mim #ID: 2013-2-50-002 Nusrat Jahan #ID: 2012-3-50-001 Under the supervision of Dr. Mohamed Ruhul Amin Professor Dept. of Electronics and Communication Engineering East West University & Dr. Md. Imdadul Islam Professor Dept. of Computer Science and Engineering Jahangirnagar University Dept. of ECE @ EWU Page 1 DECLARATION We hereby declare that we carried out the work reported in this project in the Department ofElectronics and Communications Engineering, East West University, under the supervision ofDr. Mohamed Ruhul Amin and Dr. Md. Imdadul Islam. We solemnly declare that to the best of our knowledge, no part of this report has been submitted elsewhere for award of a degree. All sources of knowledge usedhave been duly acknowledged. Signature: ----------------------------------------- ------------------------------------------ SharminAkterMim Nusrat Jahan ID: 2013-2-50-002 ID: 2012-3-50-001 ------------------------------------- Supervisor Dr. Mohamed Ruhul Amin Professor, Dept. of Electronics and Communication Engineering East West University & ------------------------------------- Supervisor Dr. Md. Imdadul Islam Professor, Dept. of Computer Science and Engineering Jahangirnagar University Dept. of ECE @ EWU Page 2 CERTIFICATE This is to certify that the major project entitled “Determination of Optimum Step Size of LMS Algorithm in De-noising of Image” being submitted by Sharmin Akter Mim and Nusrat Jahan of Electronics and Communications Engineering Department, East West University, Dhaka in partial fulfillment for the award of the degree of Bachelor of Science in Information and Communication Engineering, is a record of major project carried out by them.
    [Show full text]
  • Adaptive Digital Filters Branko Kovacˇevic´ • Zoran Banjac Milan Milosavljevic´
    Adaptive Digital Filters Branko Kovacˇevic´ • Zoran Banjac Milan Milosavljevic´ Adaptive Digital Filters Academic Mind University of Belgrade - School of Electrical Engineering University Singidunum, Belgrade Springer-Verlag Berlin Heidelberg Branko Kovacˇevic´ Milan Milosavljevic´ University of Belgrade University of Belgrade and Singidunum Belgrade University Serbia Belgrade Serbia Zoran Banjac School of Electrical and Computing Engineering of Applied Studies Belgrade Serbia ISBN 978-3-642-33560-0 ISBN 978-3-642-33561-7 (eBook) DOI 10.1007/978-3-642-33561-7 Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2013935402 ISBN of Academic Mind : 978-86-7466-434-6 Ó Academic Mind Belgrade and Springer-Verlag Berlin Heidelberg 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer and Academic Mind. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center.
    [Show full text]
  • Implementation of Adaptive Filtering Algorithms for Noise Cancellation
    FACULTY OF ENGINEERING AND SUSTAINABLE DEVELOPMENT Department of Electronics, Mathematics and Natural Sciences Implementation of adaptive filtering algorithms for noise cancellation Tanja Lampl 2020 Student thesis, Advanced level (Master degree), 15 HE Electronics Master Programme in Electronics/Automation (online) Supervisor: José Chilo (PhD) Examiner: Niclas Björsell (PhD) i Abstract This paper deals with the implementation and performance evaluation of adaptive filtering algorithms for noise cancellation without reference signal. Noise cancellation is a technique of estimating a desired signal from a noise- corrupted observation. If the signal and noise characteristics are unknown or change continuously over time, the need of adaptive filter arises. In contrast to the conventional digital filter design techniques, adaptive filters do not have constant filter parameters, they have the capability to continuously adjust their coefficients to their operating environment. To design an adaptive filter, that produces an optimum estimate of the desired signal from the noisy environment, different adaptive filtering algorithms are implemented and compared to each other. The Least Mean Square LMS, the Normalized Least Mean Square NLMS and the Recursive Least Square RLS algorithm are investigated. Three performance criteria are used in the study of these algorithms: the rate of convergence, the error performance and the signal-to- noise ratio SNR. The implementation results show that the adaptive noise cancellation application benefits more from
    [Show full text]
  • Analysis of Adaptive Filter Algorithms with an Application to Harmonic
    Analysis of Adaptive Filter Algorithms with an Application to Harmonic Noise Cancellation in Distribution Power Line Communications by Jin-Der Wang Center for Communications and Signal Processing Department of Electrical and Computer Engineering North Carolina State University August 1985 CCSP-TR-85/15 ABSTRACT WANG, JIN-DER. Analysis of Adaptive filter Algorithms with an Application to Harmonic Noise Cancellation in Distribution Power Line Communications. (Under the direction of Dr. Henry Joel Trussell.) Some well-known adaptive algorithms such as the least mean squares (LMS) and the recursive least squares (RLS) algorithms are reviewed, and the properties of some newly developed fast RLS algorithms such as the fast Kalman (FK), the fast a priori estimation sequential technique (FAEST), and the fast transversal filter (FTF) algorithms are investigated. These adaptive algorithms are applied to the problem of harmonic noise cancellation in distribution power line communica­ tions. The fast RLS algorithms were derived independently, from different approaches, and no connection had previously been made. They are rederived with a unified approach, and their mathematical equivalence is shown by examining certain algorithmic quantities and initial conditions. Based on this work, an improved rescue variable is then proposed which can detect the tendency of algo­ rithm divergence earlier than previously proposed rescue variables. Adaptive filters are applied to harmonic noise cancellation m distribution power line communications. It is shown that most filter taps can be constrained to zero to reduce computational complexity. The constrained LMS and RLS algo­ rithms are derived for a general constraint problem, and the constrained FK algorithm is derived for harmonic noise cancellation.
    [Show full text]