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‎.gitignore

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TSWLatexianTemp*
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## Editors:
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# GEdit
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*.tex~
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# WinEdt
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*.bak
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*.sav

‎README.md

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# adaptiveFilteringLectureNotes
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# adaptiveFilteringLectureNotes
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The present lecture notes were written for the annual course on adaptive filters at Aalborg University. The content of the course is now a part of the annual course called *Array and Sensor Signal Processing*. The notes are written for the lecturer, but they may also be useful to the student as a supplement to his/her favourite textbook. Consequently, the notes are very concise and contain only what we believe to be the basics of adaptive filtering. Moreover, we have also made some important simplifications.
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- We use real-valued numbers and not complex-valued numbers. Although the latter is more general, it is less confusing and leads to fewer errors when real-valued numbers are used.
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- We only consider FIR adaptive filters.
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- The signals have zero mean. This is a standard assumption used in most textbooks.
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Each of the lectures contains an amount of material suited for a lecture lasting for approximately 90 minutes. The appendices contain a summary and some supplementary material.
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These lecture notes are always work in progress. Therefore, if you have found an error, have a suggestion for a better statement and/or explanation, or just want to give us some feedback, then do not hesitate to contact us.

‎lecture_notes/Makefile

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##################################################################
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# Makefile for LaTeX
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##################################################################
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# Use:
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# make
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# make clean
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# options for ps2pdf: http://pages.cs.wisc.edu/~ghost/doc/AFPL/6.50/Ps2pdf.htm
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TEX:=$(shell ls *.tex)
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PS=$(TEX:.tex=.ps)
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OTHER = *~ *.aux *.dvi *.toc *.bbl *.blg *.out *.thm *.tdo *.auxlock figures/*.dpth figures/*.log *.figlist
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pdflatex: lecture_notes.tex
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pdflatex -shell-escape -synctex=1 lecture_notes.tex
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bibtex lecture_notes
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pdflatex -shell-escape -synctex=1 lecture_notes.tex
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pdflatex -shell-escape -synctex=1 lecture_notes.tex
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cp lecture_notes.pdf lecture_notes.screen.pdf
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rm -f $(OTHER) $(PS)
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print: lecture_notes.tex
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pdflatex -shell-escape -synctex=1 '\newcommand{\type}{print}\input{lecture_notes.tex}'
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bibtex lecture_notes
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pdflatex -shell-escape -synctex=1 '\newcommand{\type}{print}\input{lecture_notes.tex}'
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pdflatex -shell-escape -synctex=1 '\newcommand{\type}{print}\input{lecture_notes.tex}'
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rm -f $(OTHER) $(PS)
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cp lecture_notes.pdf lecture_notes.print.pdf
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#figure: lecture_notes.tex
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# pdflatex -shell-escape -jobname=figures/$(figname) lecture_notes.tex #--shell-escape enables calls to external programs such as gnuplot
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# (cd figures && rm -f $(OTHER) *.table *.gnuplot *.log)
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clean:
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rm -f $(OTHER) $(PS)

‎lecture_notes/bib/mybib.bib

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@Book{Lay2005,
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Title = {Linear algebra and its applications},
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Author = {David C. Lay},
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Publisher = {Pearson/Addison-Wesley},
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Year = {2005},
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Edition = {3},
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Month = {Sep.},
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Owner = {jkjaer},
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Timestamp = {2011.03.02}
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}
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@Book{Strang2009,
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Title = {Introduction to Linear Algebra},
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Author = {Gilbert Strang},
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Publisher = {Wellesley Cambridge Press},
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Year = {2009},
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Edition = {4},
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Month = {Feb.},
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Owner = {jkjaer},
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Timestamp = {2011.03.02}
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}
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@Book{Antoniou2007,
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Title = {Practical Optimization: Algorithms and Engineering Applications},
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Author = {Andreas Antoniou and Wu-Sheng Lu},
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Publisher = {Springer},
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Year = {2007},
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Month = {Mar.},
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Owner = {jkjaer},
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Timestamp = {2011.03.01}
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}
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@Book{Kay2005,
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Title = {Intuitive Probability and Random Processes using {MATLAB}},
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Author = {S. M. Kay},
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Publisher = {Springer Science, New York, Inc.},
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Year = {2006},
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ISBN = {0387241574}
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}
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@Book{Leon-Garcia2008,
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Title = {Probability, Statistics, and Random Processes For Electrical Engineering},
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Author = {Alberto Leon-Garcia},
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Publisher = {Prentice Hall},
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Year = {2008},
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Edition = {3},
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Month = {Jan.},
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Owner = {jkjaer},
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Timestamp = {2011.03.02}
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}
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@Book{Sayed2003,
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Title = {Fundamentals of Adaptive Filtering},
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Author = {Ali H. Sayed},
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Publisher = {Wiley-IEEE Press},
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Year = {2003},
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Month = {Jun.},
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Owner = {jkjaer},
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Timestamp = {2011.02.16}
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}
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@Book{Haykin2001,
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Title = {Adaptive Filter Theory},
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Author = {Simon Haykin},
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Publisher = {Prentice Hall},
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Year = {2001},
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Edition = {4},
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Month = {Sep.},
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Owner = {jkjaer},
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Timestamp = {2011.01.26}
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}
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@Article{Shin2004,
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Title = {Mean-Square Performance of a Family of Affine Projection Algorithms},
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Author = {Hyun-Chool Shin and Ali H. Sayed},
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Journal = IEEE_J_SP,
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Year = {2004},
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Month = {Jan.},
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Number = {1},
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Pages = {90--102},
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Volume = {52},
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Owner = {jkjaer},
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Timestamp = {2011.02.24}
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}
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@Book{Hayes1996,
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Title = {Statistical Digital Signal Processing and Modeling},
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Author = {Monson H. Hayes},
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Publisher = {Wiley},
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Year = {1996},
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Owner = {jkjaer},
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Pages = {Mar.},
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Timestamp = {2011.02.24}
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}
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@Article{Slock1991,
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Title = {Numerically stable fast transversal filters for recursive least squares adaptive filtering},
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Author = {Slock, D. T. M. and Kailath, T.},
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Journal = IEEE_J_SP,
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Year = {1991},
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Month = {Jan.},
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Number = {1},
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Pages = {92--114},
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Volume = {39},
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ISSN = {1053-587X}
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}
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@Misc{Petersen2008,
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Title = {The Matrix Cookbook},
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Author = {K. B. Petersen and M. S. Pedersen},
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HowPublished = {Online},
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Month = {oct},
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Note = {Version 20081110},
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Year = {2008},
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Abstract = {Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices.},
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Keywords = {Matrix identity, matrix relations, inverse, matrix derivative},
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Publisher = {Technical University of Denmark},
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Url = {http://www2.imm.dtu.dk/pubdb/p.php?3274}
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}

‎lecture_notes/figures/block_diagram_w_feedback.pdf

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‎lecture_notes/figures/const_opt.pdf

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‎lecture_notes/figures/exponential_window.ew.gnuplot

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set table "figures/exponential_window.ew.table"; set format "%.5f"
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set samples 100.0; plot [x=0:7] 0.70**(7-x)

‎lecture_notes/figures/exponential_window.ew.table

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# Curve 0 of 1, 100 points
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# Curve title: "0.70**(7-x)"
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# x y type
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0.00000 0.08235 i
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0.07071 0.08446 i
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‎lecture_notes/figures/exponential_window.pdf

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‎lecture_notes/figures/growing_window.pdf

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‎lecture_notes/figures/learning_curve_sd.J.gnuplot

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set table "figures/learning_curve_sd.J.table"; set format "%.5f"
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set samples 100.0; plot [x=0:6] 0.25+3*2**(-2*x-1)

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