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    SystemVue 2010.012010

    Examples

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    Agilent Technologies, Inc. 2000-2009395 Page Mill Road, Palo Alto, CA 94304 U.S.A.No part of this manual may be reproduced in any form or by any means (includingelectronic storage and retrieval or translation into a foreign language) without prioragreement and written consent from Agilent Technologies, Inc. as governed by UnitedStates and international copyright laws.

    Acknowledgments Mentor Graphics is a trademark of Mentor Graphics Corporation inthe U.S. and other countries. Microsoft, Windows, MS Windows, Windows NT, andMS-DOS are U.S. registered trademarks of Microsoft Corporation. Pentium is a U.S.registered trademark of Intel Corporation. PostScript and Acrobat are trademarks ofAdobe Systems Incorporated. UNIX is a registered trademark of the Open Group. Javais a U.S. trademark of Sun Microsystems, Inc. SystemC is a registered trademark ofOpen SystemC Initiative, Inc. in the United States and other countries and is used withpermission. MATLAB is a U.S. registered trademark of The Math Works, Inc.. HiSIM2source code, and all copyrights, trade secrets or other intellectual property rights in and tothe source code in its entirety, is owned by Hiroshima University and STARC.

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    Adaptive Equalization Library ExamplesPath: Examples\Adaptive Equalization Library

    Name Description Usage

    BlindEqLms.wsv This example implements a blind equalizer. The adaptive filter LMScore block is used as the adaptive algorithm. Note that in this case thedesired signal is the output of the non linearity block. This means thatno training sequence is required.

    DFE_Example.wsv

    EqualiserCoreRLS.wsv This example shows the use of the Complex RLS Adaptive Filter Coreblock in an inverse system identification scenario. An equivalentimplementation using the Complex RLS Adaptive Filter is alsoprovided. Note that the Complex RLS Adaptive Filter Core block onlyimplements the complex FIR filter with variable coefficients and theadaptive RLS algorithm controlling them. Therefore the subtractor anderror feedback loop need to be implemented externally when using theComplex RLS Adaptive Filter Core block.

    EqualiserRealRLS.wsv This example shows the use of the Real RLS Adaptive Filter block in aninverse system identification scenario.

    EqualiserRealRLSCore.wsv This example shows the use of the Real RLS Adaptive Filter Core blockin an inverse system identification scenario. An equivalentimplementation using the Real RLS Adaptive Filter is also provided.Note that the Real RLS Adaptive Filter Core block only implements thereal FIR filter with variable coefficients and the adaptive RLS algorithmcontrolling them. Therefore the subtractor and error feedback loopneed to be implemented externally when using the Real RLS AdaptiveFilter Core block.

    InverseSysIdAPACore.wsv This model implements a complex arithmetic inverse systemidentification setup using the APA algorithm. The unknown system is acomplex FIR filter. The error signal is plotted once it has gone throughthe error filter. The identified filter weights are also plotted. Note thatthey represent the inverse of the impulse response of the unknownfilter. The frequency response of both unknown channel and equalizerare also plotted.

    InverseSysIdRealAPACore.wsv This model implements a real arithmetic inverse system identificationsetup using the APA algorithm. The unknown system is a real FIRfilter. The error signal is plotted once it has gone through the errorfilter. The identified filter weights are also plotted. Note that theyrepresent the inverse of the impulse response of the unknown filter.The frequency response of both unknown channel and equalizer arealso plotted.

    SysIdAPA.wsv In this example a system identification configuration has been setup,where the adaptive filter attempts to identify the impulse response ofa complex arithmetic unknown system. Both the unknown system andthe adaptive filter are excited with white noise. The unknown system isrepresented here by a complex FIR filter. Its output is used as thedesired signal input of the adaptive filter as shown.

    SysIdLMS.wsv In this example a system identification configuration has been setup,where the adaptive filter attempts to identify the impu