All pages
 
All pages | Previous page (LRVC Dec6)
Lecture37ECE438F14Lecture37 blog ECE302S13 BoutinLecture38ECE438F10
Lecture38ECE438F11Lecture38ECE438F13Lecture38ECE438F14
Lecture38 blog ECE302S13 BoutinLecture39ECE438F10Lecture39ECE438F11
Lecture39ECE438F13Lecture39ECE438F14Lecture39 blog ECE302S13 Boutin
Lecture3ECE301S11Lecture3ECE400F13Lecture3ECE400F14
Lecture3ECE400S12Lecture3ECE400S14Lecture3ECE438F10
Lecture3ECE438F11Lecture3ECE438F13Lecture3ECE438F14
Lecture3ECE438F15Lecture3ECE662S10Lecture3ECE662S12
Lecture3 blog ECE302S13 BoutinLecture3 video ECE637 Image Processing 1 BoumanLecture40ECE438F10
Lecture40ECE438F11Lecture40ECE438F13Lecture40ECE438F14
Lecture40 blog ECE302S13 BoutinLecture41ECE438F10Lecture41ECE438F11
Lecture41ECE438F13Lecture41ECE438F14Lecture41 blog ECE302S13 Boutin
Lecture42ECE438F10Lecture42ECE438F11Lecture42ECE438F13
Lecture42ECE438F14Lecture42 blog ECE302S13 BoutinLecture43ECE438F10
Lecture43ECE438F11Lecture43ECE438F13Lecture43ECE438F14
Lecture43 blog ECE302S13 BoutinLecture44ECE438F10Lecture44ECE438F11
Lecture44ECE438F13Lecture44ECE438F14Lecture44 blog ECE302S13 Boutin
Lecture49 blog ECE302S13 BoutinLecture4ECE301S11Lecture4ECE400F13
Lecture4ECE400F14Lecture4ECE400S12Lecture4ECE400S14
Lecture4ECE438F10Lecture4ECE438F11Lecture4ECE438F13
Lecture4ECE438F14Lecture4ECE438F15Lecture4ECE662S10
Lecture4ECE662S12Lecture4 ECE301Fall2008mboutinLecture4 blog ECE302S13 Boutin
Lecture4 video ECE637 Image Processing 1 BoumanLecture5ECE301S11Lecture5ECE400F13
Lecture5ECE400F14Lecture5ECE400S12Lecture5ECE400S14
Lecture5ECE438F10Lecture5ECE438F11Lecture5ECE438F13
Lecture5ECE438F14Lecture5ECE438F15Lecture5ECE662S10
Lecture5ECE662S12Lecture5 ECE301Fall2008mboutinLecture5 blog ECE302S13 Boutin
Lecture5 video ECE637 Image Processing 1 BoumanLecture6ECE301S11Lecture6ECE400F13
Lecture6ECE400F14Lecture6ECE400S12Lecture6ECE400S14
Lecture6ECE438F10Lecture6ECE438F11Lecture6ECE438F13
Lecture6ECE438F14Lecture6ECE662S10Lecture6ECE662S12
Lecture6 blog ECE302S13 Boutin
Lecture6 blog ECE400S12
Lecture6 video ECE637 Image Processing 1 Bouman
Lecture7ECE301S11Lecture7ECE400F13Lecture7ECE400F14
Lecture7ECE400S12Lecture7ECE400S14Lecture7ECE438F10
Lecture7ECE438F11Lecture7ECE438F13Lecture7ECE438F14
Lecture7ECE662S10Lecture7ECE662S12Lecture7 blog ECE302S13 Boutin
Lecture7 video ECE637 Image Processing 1 BoumanLecture8ECE301S11Lecture8ECE400F13
Lecture8ECE400F14Lecture8ECE400S12Lecture8ECE400S14
Lecture8ECE438F10Lecture8ECE438F11Lecture8ECE438F13
Lecture8ECE438F14Lecture8ECE662S10Lecture8ECE662S12
Lecture8 blog ECE302S13 BoutinLecture8 video ECE637 Image Processing 1 BoumanLecture9ECE301S11
Lecture9ECE400F13Lecture9ECE400F14Lecture9ECE400S12
Lecture9ECE400S14Lecture9ECE438F10Lecture9ECE438F11
Lecture9ECE438F13Lecture9ECE438F14Lecture9ECE662S12
Lecture9 blog ECE302S13 BoutinLecture9 video ECE637 Image Processing 1 BoumanLectureECE264Spring12
LectureScheduleECE302Spring13 BoutinLecture 1Lecture 1, 8/24/2009 (ECE 438 Fall09)
Lecture 10 - Batch Perceptron and Fisher Linear Discriminant OldKiwiLecture 10 - Batch Perceptron and Fisher Linear Discriminant Old KiwiLecture 10 online ECE301S11 Prof Boutin
Lecture 11 - Fischer's Linear Discriminant again OldKiwiLecture 11 - Fischer's Linear Discriminant again Old KiwiLecture 11 ECE264F12Lu
Lecture 11 OldKiwi
Lecture 11 Old Kiwi
Lecture 12 - Support Vector Machine and Quadratic Optimization Problem OldKiwi
Lecture 12 - Support Vector Machine and Quadratic Optimization Problem Old KiwiLecture 12 ECE264F12LuLecture 13-2/21/2012-Kailu Song lecturen notes
Lecture 13 - Kernel function for SVMs and ANNs introduction OldKiwiLecture 13 - Kernel function for SVMs and ANNs introduction Old KiwiLecture 13 ECE264F12Lu
Lecture 14 - ANNs, Non-parametric Density Estimation (Parzen Window) OldKiwiLecture 14 - ANNs, Non-parametric Density Estimation (Parzen Window) Old KiwiLecture 14 ECE264F12Lu
Lecture 15 - Parzen Window Method OldKiwiLecture 15 - Parzen Window Method Old KiwiLecture 15 ECE264F12Lu
Lecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate OldKiwiLecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate Old KiwiLecture 17 - Nearest Neighbors Clarification Rule and Metrics OldKiwi
Lecture 17 - Nearest Neighbors Clarification Rule and Metrics Old KiwiLecture 17 Mar9Lecture 18 - Nearest Neighbors Clarification Rule and Metrics(Continued) OldKiwi
Lecture 18 - Nearest Neighbors Clarification Rule and Metrics(Continued) Old KiwiLecture 18 ECE264F12LuLecture 19
Lecture 19 - Nearest Neighbor Error Rates OldKiwiLecture 19 - Nearest Neighbor Error Rates Old KiwiLecture 1 - Introduction OldKiwi
Lecture 1 - Introduction Old KiwiLecture 1 MA181Fall2008bellLecture 20
Lecture 20 - Density Estimation using Series Expansion and Decision Trees OldKiwiLecture 20 - Density Estimation using Series Expansion and Decision Trees Old KiwiLecture 21 - Decision Trees(Continued) OldKiwi
Lecture 21 - Decision Trees(Continued) Old KiwiLecture 22 - Decision Trees and Clustering OldKiwiLecture 22 - Decision Trees and Clustering Old Kiwi
Lecture 23 - Spanning Trees OldKiwiLecture 23 - Spanning Trees Old KiwiLecture 24 - Clustering and Hierarchical Clustering OldKiwi
Lecture 24 - Clustering and Hierarchical Clustering Old KiwiLecture 25 - Clustering Algorithms OldKiwiLecture 25 - Clustering Algorithms Old Kiwi
Lecture 26 - Statistical Clustering Methods OldKiwiLecture 26 - Statistical Clustering Methods Old KiwiLecture 27
Lecture 27 - Clustering by finding valleys of densities OldKiwiLecture 27 - Clustering by finding valleys of densities Old KiwiLecture 28 - Final lecture OldKiwi
Lecture 28 - Final lecture Old KiwiLecture 2 - Decision Hypersurfaces OldKiwiLecture 2 - Decision Hypersurfaces Old Kiwi
Lecture 2 OldKiwi
Lecture 2 Old Kiwi
Lecture 3
Lecture 3 - Bayes Theorem and its Application to Pattern Recognition OldKiwi
Lecture 3 - Bayes classification OldKiwiLecture 3 - Bayes classification Old Kiwi
Lecture 3 OldKiwi
Lecture 3 Old Kiwi
Lecture 4 - Bayes Classfication OldKiwi
Lecture 4 - Bayes Classfication Old Kiwi
Lecture 4 - Bayes Classification OldKiwiLecture 4 - Bayes Classification Old Kiwi
Lecture 4 OldKiwi
Lecture 4 Old Kiwi
Lecture 5 - Discriminant Functions OldKiwi
Lecture 5 - Discriminant Functions Old KiwiLecture 5 ECE302Fall2008sanghaviLecture 6
Lecture 6 - Discriminant Functions OldKiwiLecture 6 - Discriminant Functions Old Kiwi
Lecture 6 ECE302Fall2008sanghavi
Lecture 7Lecture 7 - MLE and BPE OldKiwiLecture 7 - MLE and BPE Old Kiwi
Lecture 7 OldKiwi
Lecture 7 Old Kiwi
Lecture 8
Lecture 8 - MLE, BPE and Linear Discriminant Functions OldKiwiLecture 8 - MLE, BPE and Linear Discriminant Functions Old Kiwi
Lecture 8 OldKiwi
Lecture 8 Old Kiwi
Lecture 9Lecture 9 - Linear Discriminant Functions OldKiwi
Lecture 9 - Linear Discriminant Functions Old KiwiLecture Blog ECE438 F10Lecture Notes 9-9-09
Lecture Notes ECE438 HW3Lecture Notes MA181Fall2008bellLecture Prof. Elmqvist 3/21 ipa 2-1
Lecture QuestionsLecture Schedule (ECE438BoutinSpring09)Lecture Schedule ECE301Spring11 Boutin
Lecture Schedule ECE301Spring18 BoutinLecture Schedule ECE438Fall10 BoutinLecture Schedule ECE438Fall11 Boutin
Lecture Schedule ECE438Fall13 BoutinLecture Schedule ECE438Fall14 BoutinLecture Schedule ECE438Fall15 Boutin
Lecture Schedule ECE438Fall16 BoutinLecture Schedule ECE438Fall2019 BoutinLecture Schedule ECE438Spring17 Boutin
Lecture for IPA2-5Lecture notes by aashish simhaLectures
LegendreMA527Fall2010Lemma boutin mhossain 05 2013Lemma for 7-1 OldKiwi
Lemma for 7-1 Old KiwiLetter advice incoming students ECE bonus ethics ECE400F13Likelihood Principle OldKiwi
Likelihood Principle Old KiwiLimits Approaching Infinity ConceptuallyLimits Approaching Infinity Intuitively
Limits of functionsLindsay Middleton's Favorite TheoremLinearClassierSlectureJMS
LinearClassifierSlecture reviewLinearDependence MA265Fall2011WaltherLinear Algebra Resource
Linear Algebra done ConceptuallyLinear Algebra the Conceptual WayLinear Algebra the Conceptual way
Linear Algebra the Intuitive WayLinear Discriminant Functions (LDF) OldKiwiLinear Discriminant Functions (LDF) Old Kiwi
Linear Discriminant Functions OldKiwiLinear Discriminant Functions Old KiwiLinear Equations/Matrices MA265S12Walther
Linear MMSE Estimator Example (12/1) ECE302Fall2008sanghaviLinear Systems of ODEsLinear algebra
Linear algebra (complex numbers)Linear algebra (eigenvalues and eigenvectors)Linear algebra courses
Linear algebra in engineering MA265F12AlvaradoLinear algebra slecturesLinear algebra tutorials
Linear combinationLinear combinations of independent gaussian RVsLinear dependence
Linear discriminant functions OldKiwiLinear discriminant functions Old KiwiLinear programming MA265F11Walther
Linear transformationLinearity Spring 2011Linearity of a system ECE301S11
Lineariy of expectation proof mhossainLinearly IndependentLink
Link titleLinks to pattern recognition at other universities OldKiwiLinks to pattern recognition at other universities Old Kiwi
Linley Johnson's Favorite TheoremList of Course WikisLog polar transform
LoginBountyLogistic ModelsLossy versus Lossless Images
Lu Zhang -- Nyquist sampling theoremLu Zhang - Homework 2.6Luke's Exam OldKiwi
Luke's Exam Old KiwiMA181MA181Fall2008bell:About MA181Fall2008bell
MA181Fall2008bell:General disclaimer MA181Fall2008bellMA181Fall2008bell:Privacy policy MA181Fall2008bellMA181Fall2008bell talk:About MA181Fall2008bell
MA182 (McClureSpring2009)MA265MA265F12Alvarado
MA265Fall2012AlvaradoMA265HemanthMA265RHEAHMULLANG
MA265Spring2010WaltherMA266MA271Fall2020Walther Topic27 Concepts to Know Before Learning About Penrose Tiling
MA271Fall2020Walther Topic27 First Penrose Tiling/Original Pentagonal Tiling (P1)MA271Fall2020Walther Topic27 Golden RatioMA271Fall2020Walther Topic27 Inflation and Deflation
MA271Fall2020Walther Topic27 IntroductionMA271Fall2020Walther Topic27 QuasicrystalsMA271Fall2020Walther Topic27 Real World Examples
MA271Fall2020Walther Topic27 ReferencesMA271Fall2020Walther Topic27 Robinson TrianglesMA271Fall2020Walther Topic27 Rules for Generating Penrose Tilings
MA271Fall2020Walther Topic27 Second Penrose Tiling/Kite and Dart Tiling (P2)MA271Fall2020Walther Topic27 Third Penrose Tiling/Rhombus Tiling (P3)MA279
MA279Fall2013WaltherMA279Fall2018Penrose HistoryMA279Fall2018Penrose Introduction
MA279Fall2018Penrose MethodsMA279Fall2018Penrose QuasicrystalsMA279Fall2018Penrose References
MA279Fall2018Topic12 BackgroundMA279Fall2018Topic1 Counting BeesMA279Fall2018Topic1 Counting Rabbits
MA279Fall2018Topic1 FlowersMA279Fall2018Topic1 IntroductionMA279Fall2018Topic1 Leaves
Previous page (LRVC Dec6)
Retrieved from "https://www.projectrhea.org/rhea/index.php/Special:AllPages"
Shortcuts
Help Main Wiki Page Random Page Special Pages Log in
Search

Alumni Liaison

Prof. Math. Ohio State and Associate Dean
Outstanding Alumnus Purdue Math 2008

Jeff McNeal