基于Matlab实现的指纹图像细节特征提取
很实用的程序，详细介绍了如何实用软件识别指纹。几乎完全不懂得人也可用DO+ p1+p2+p3+p5+p6+4][5Qif(n==7|n==56(t)M ahbdpbt(y(j,x(i),’bo);6化正像细化处理图信c)特证液果for i=1:t-15d= sqrt((x(i)-x(D)2+(y(i)-y(j)2);FV C2000100if d< %100typeI(1)=Qbreakb1(i=o1944-2011ChinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net9436[2MATLAB 6.5 M.152003-3.LD I1/3,2002-513(5):946~956[5 Dario m ai m em ber Eee, and d av de m alon i d irect grayscalem inu tae detection in fingerpr ints J]. EEE tran sactions onpat te m analys s and m ach ine inte lligen ce 1997 19(1): 27-40M ahbMATLAB 6 5[M]2004-51/3(19815-),((1947-),([1] R Clarke Hum an ien tification in in fom at ion systen s M anagem ent ch allenges and pub le policy issues[ J. In fo T echnol People1994,7(4):6~37.(1978.1-),()113)[3 S Coleri M Ergen A Pu ri and A Bahai Channel E stim ationTechn iqu es Based on Pilot a range ent in OFDM System s[ JIL abV IEWwireEEE T ran sact in s on Broadcast ing Sep 2002 48( 3):223lessan-ofdm229[4 X Tang M a buini and a JGo Hsm ith E fect of Channel Est im artion E rror on M-QAM BER Perfm ance in Ray le igh Fad ing J IEEE T ran sactions On Commun ications Dec 1999, 47(121856LabV ieWieee 802 1 6d[5 P Das and D Koch On the U se ofV iu al Programm ng LanguagesO FDMfor Commun ication System Sim ulation[C IEEE Proceedings ofSoutheast Con, Apr 1991(BER)[6 M C Jeruch m, P B alb an and K s Shanmugan Simu lat ion oBERCommun ica tion Sy stems M odeling M ethodology and Techn iques[J. K hw er A cadem i 2000BER[7] V. Erceg L J ste in SY Tindra SR Parkoff A G up ta BKulic A a Julius and R B inchi An Em p irically Based Path LossIeee 802 16dOFDMM odel for W ire kss Ch annes in Suburban Environm ents[ J]. EEEJoumal on Selected A reas in C mmun ica tions Ju I 1999(197610-),[1] IKoffm an and v Rom an. Broadband W iess a ccess So hi tionsBased on O FDM A ccess in 802 16[ J IEEE Camm unicat ionsM agazne, A pr 2002(19659-),(),[21 EKlund R BM arks K L Stanwood and Sw ang IEEE Standard802. 16a a Techn ical very iew of thew ireless antm a ir In ter(19776-),(face for B roa dband W ire less access[ J]. IEEE Camm unicat ionsM agaz ne Jun200240(6):98-107185o1994-2011ChinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net
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Adaptive Filters
自适应滤波器的权威Sayed的大作，用大量的实例诠释自适应滤波器的各种算法原理，是不可多得的好书。ADAPTIVE FILTERSADAPTIVE FILTERSALIH SAYEDUniversity of California at Los Angeles◆旧EEEIEEE PressWIlEYNTERSCIENCEA JOHN WILEY SONS, INC, PUBLICATIONCover design by Michael RutkowskiCopyright C 2008 by John Wiley Sons, Inc. All rights reservedPublished by John Wiley Sons, Inc, Hoboken, New JerseyPublished simultaneously in CanadaNo part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or bymeans, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under anySection 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of thePublisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center,Inc, 222 Rosewood Drive, Danvers, MA01923, (978)750-8400, fax(978)750-4470, or on the web atwww.copyright.comRequeststothePublisherforpermissionshouldbeaddressedtothePermissionsDepartment, John Wiley sons, Inc, 111 River Street, Hoboken, NJ,(201)748-6011, fax(201)748-6008,oronlineathttp:/www.wiley.com/go/permissionLimit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts inpreparing this book, they make no representations or warranties with respect to the accuracy or completeness ofe contents of this book and specifically disclaim any implied warranties of merchantability or fitness for aarticular purpose. No warranty may be created or extended by sales representatives or written sales materialsThe advice and strategies contained herein may not be suitable for your situation. You should consult with aprofessional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or anyother commercial damages, including but not limited to special, incidental, consequential, or other damagesFor general information on our other products and services or for technical support, please contact our CustomerCare Department within the United States at(800)762-2974, outside the United States at (317)572-3993 or fax(317)572-4002Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not beavailable in electronic formats. For more information about wiley products, visit our web site atwww.wlley.conLibrary of Congress Cataloging-in-Publication Data:Sayed, Ali hAdaptive filters/Ali H. Sayedp cmIncludes bibliographical references and indexISBN9780470-25388-5( cloth)Adaptive filters. I. TitleTK7872F5s285200862138l5324dc222008003731Printed in the united states of america10987654321To my parentsContentsPrefacexviiNotationXXVAcknowledgmentsXXXBACKGROUND MATERIALA Random variablesA 1 Variance of a random variableA2 Dependent random VariablesA3 Complex-Valued Random VariablesA 4 Vector -Valued Random variables3467A.5 Gaussian Random VectorsB Linear Algebra12B. Hermitian and Positive- Definite matricesB 2 Range spaces and nullspace of matrices14B3 Schur Complements16B 4 Cholesky factorizationB 5 QR DecompositionB6 Singular Value Decomposition20B 7 Kronecker productsC Complex Gradients25C 1 Cauchy-Riemann Conditions5C2 Scalar arguments26C3 Vector arguments26PART:。 PTIMAL ESTIMATIONScalar- Valued Data291. 1 Estimation Without observations1.2 Estimation Given Dependent observations1.3 Orthogonality Principl36CONTENTS1,4 Gaussian random variables382 Vector- Valued Data422. 1 Optimal Estimator in the vector Case422.2 Spherically Invariant Gaussian Variables462. 3 Equivalent Optimization Criterion49Summary and Notes51Problems and Computer Projects54PART I: LINEAR ESTIMATION3 Normal Equatlons603. 1 Mean-Square Error Criterion613.2 Minimization by Differentiation3.3 Minimization by Completion-of-Squares633.4 Minimization of the error Covariance matrix653.5 Optimal Linear estimator4 Orthogonality princlple4. 1 Design Examples4.2 Orthogonality Condition4.3 Existence of solutions744, 4 Nonzero-Mean variables5 Linear Models5.1 Estimation using Linear Relations5.2 Application: Channel Estimation5Application: Block Data Estimation815. 4 Application: Linear Channel equalization825.5 Application: Multiple-Antenna Receivers85Constralned estimation876.1 Minimum-Variance Unbiased estimation6.2 Example: Mean Estimation6.3 Application: Channel and Noise Estimation916.4 Application: Decision Feedback Equalization6.5 Application: Antenna Beamforming1017 Kalman Filter1047.1 Innovations process7.2 State-Space Model106
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