digital signal processing using matlab pdf free download

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... Rao, C.R., Effects of estimated noise covariance matrix in optimal signal detection, IEEE Trans. on Acoustics, Speech, and Signal Processing, ASSP-35(5), 671–679, May 1987. [21] Cai, L.andWang, ... algorithm, Proc. Signal and Data Processing of Small Targets, SPIE Proc. Series, Vol. 1305, Paper 16, 180–192, Orlando, FL, April 16-18, 1990. [27] Wang, H. and Cai, L., On adaptive multiband signal detection ... for adaptive suppression, free from strong clutter contamination. Available acquisition methods include the use of clutter -free range-cells for low PRF systems, clutter -free Doppler bins for high...

Ngày tải lên: 13/12/2013, 00:15

... multiuser communications, IEEE Trans. on Signal Processing, Special Issue on Signal Processing for Advanced Communications, 45(1), Jan. 1997. [10] Ding, Z., Blind channel identification and equalization using spectral ... IntroductionandMotivation Thischapterreviewstheapplicationsofantennaarraysignalprocessingtomobilenetworks.Cellular networksarerapidlygrowingaroundtheworldandanumberofemergingtechnologiesareseentobe criticaltotheirimprovedeconomicsandperformance.Amongtheseistheuseofmultipleantennas andspatialsignalprocessingatthebasestation.ThistechnologyisreferredtoasSmartAntennasor, moreaccurately,asSpace-TimeProcessing(STP).STPreferstoprocessingtheantennaoutputsin bothspaceandtimetomaximizesignalquality. Acellulararchitectureisusedinanumberofmobile/portablecommunicationsapplications.Cell sizesmayrangefromlargemacrocells,whichservehighspeedmobiles,tosmallermicrocellsorvery smallpicocells,whicharedesignedforoutdoorandindoorapplications.Eachoftheseoffersdifferent channelcharacteristicsand,therefore,posesdifferentchallengesforSTP.Likewise,differentservice deliverygoalssuchasgradeofserviceandtypeofservice:voice,data,orvideo,alsoneedspecic STPsolutions.STPprovidesthreeprocessingleverages.Therstisarraygain.Multipleantennas capturemoresignalenergy,whichcanbecombinedtoimprovethesignal-to-noiseratio(SNR).Next isspatialdiversitytocombatspace-selectivefading.Finally,STPcanreduceco-channel,adjacent channel,andinter-symbolinterference. Theorganizationofthischapterisasfollows.InSection68.2,wedescribethevectorchannelmodel forabasestationantennaarray.InSection68.3wediscussthealgorithmsforSTP.Section68.4outlines theapplicationsofSTPincellularnetworks.Finally,weconcludewithasummaryinSection68.5. c 1999byCRCPressLLC ... Paulraj, A., A constant modulus algorithm for multi-user signal separation in presenceof delayspread using antenna arrays, IEEE Signal Processing Letters, 4(6): 178–181, June 1997. [32] Papadias,...

Ngày tải lên: 13/12/2013, 00:15

... Some algorithms for eigensubspaceestimation, Digital Signal Processing, 5, 97–115, 1995. [36] Regalia, P.A. and Loubaton, P., Rational subspaceestimation using adaptivelossless filters, IEEE Trans. ... extending this concept to the signal subspace [8]. By sphericalizing and deflating both the signal and the noise subspaces, the cost of tracking the r dimensional signal (or noise) subspace is ... the signal subspace is not sphericalized and all of its eigencomponents are explicitly tracked whereas the noise subspace is sphericalized and not explicitly tracked (to save computation). Using...

Ngày tải lên: 13/12/2013, 00:15

... of three compo- nents: the signal y m (n) that is modeled by the adaptive filter, the signal y u (n) that is unmodeled but that depends on the input signal, and the signal v(n) that is independent ... systems, IEEE Trans. Signal Processing, 41(2), 617–628, 1993. [14] Lin, J N. and Unbehauen, R., Bias-remedy least mean square equation error algorithm for IIR parameter recursive estimation, IEEE Trans. Signal Processing, 40(1), ... Trans. Acoustics, Speech, Signal Processing, 38(7), 1222–1227, 1990. [17] Regalia, P.A., Stable and efficient latticealgorithms for adaptive IIR filtering, IEEE Trans .Signal Processing, 40(2), 375–388,...

Ngày tải lên: 13/12/2013, 00:15

... Ling, F., and Nikias, C.L., Advanced Digital Signal Processing , Macmillan Publishing, New York, 1992. [3] Widrow, B. and Stearns, S.D., Adaptive Signal Processing , Prentice-Hall, Englewood ... the signals {w i1 , à(i) r(i)} to the signals {w i , à(i) e a (i)}. Correspondingly, using (20.12), the map from the original weighted disturbance à(i)v(i) to the weighted estimation error signal à(i)e a (i) ... algorithms, IEEE Trans. Signal Processing , 44(8), 1982–1989, Aug. 1996. [19] Sayed, A.H. and Kailath, T., A state-space approach to adaptive RLS filtering, IEEE Signal Processing Magazine , 11(3),...

Ngày tải lên: 13/12/2013, 00:15

... (19.2) whereW(n)=[w 0 (n)w 1 (n)ÃÃÃw L1 (n)] T isthecoefcientvector,X(n)=[x(n)x(n 1)ÃÃÃx(nL+1)] T istheinputsignalvector,d(n)isthedesiredsignal,e(n)istheerrorsignal, andà(n)isthestepsize. TherearethreemainreasonswhytheLMSadaptivelterissopopular.First,itisrelativelyeasyto implementinsoftwareandhardwareduetoitscomputationalsimplicityandefcientuseofmemory. Second,itperformsrobustlyinthepresenceofnumericalerrorscausedbynite-precisionarithmetic. Third,itsbehaviorhasbeenanalyticallycharacterizedtothepointwhereausercaneasilysetupthe systemtoobtainadequateperformancewithonlylimitedknowledgeabouttheinputanddesired responsesignals. c 1999byCRCPressLLC [22] Farden,D.C., Tracking properties of adaptivesignal processingalgorithms, IEEETrans.Acoust., Speech, Signal Processing, ASSP-29(3), ... algorithms, IEEE Trans. Signal Processing, 41(9), 2811–2825, Sept. 1993. [25] Douglas, S.C. and Meng, T.H Y., Normalized data nonlinearities for LMS adaptation, IEEE Trans. Signal Processing, 42(6), ... Contr. Signal Processing, 4(3), 219–216, May-June 1990. [28] Harris, R.W., Chabries, D.M., and Bishop, F.A., A variable step (VS) adaptive filter algorithm, IEEE Trans. Acoust., Speech, Signal Processing, ASSP-34(2),...

Ngày tải lên: 13/12/2013, 00:15

... T., Bayesian spectrum estimation of harmonic signals, Signal Process. Lett., Vol. 2, pp. 213–215, 1995. [8] Hayes, M.S., Statistical Digital Signal Processing and Modeling, John Wiley & Sons, ... performance of some other signal and noise subspace based methods developed later. 14.5.5 Multiple Signal Classification (MUSIC) A procedure very similar to Pisarenko’s is the MUltiple SIgnal Classification ... which plays a major role in many applied sciences such as radar, speech processing, underwater acoustics, biomedical signal processing, sonar, seismology, vibration analysis, control theory, and...

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... Temporal Signals in Gaussian Noise Signal Detection: Known Gains ã Signal Detection: Unknown Gains ã Signal Detection: Random Gains ã Signal Detection: Single Signal 13.6 Spatio-Temporal Signals Detection: ... SpatialCovariance 13.7 Signal Classication Classifying Individual Signals ã Classifying Presence of Multi- ple Signals References 13.1 Introduction Detection and classification arise in signal processing ... incorporate nonzero mean [14, 15]. 13.7 Signal Classification Typical classification problems arising in signal processing are: classifying an individual signal wave- form out of a set of possible...

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... as signals and consider exploiting some of their rich signal properties in a signal processing or communication context. This perspective is illustrated graphically in Fig. 75.3, where a signal ... new circuit for communication using solitons, in Proc. IEEE Workshop on Nonlinear Signal and Image Processing, vol. I, 150–153, 1995. [14] Singer, A.C., Signal Processing and Communication with ... a loop configuration. c  1999 by CRC Press LLC Singer, A.C. Signal Processing and Communication with Solitons” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca...

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... algorithm for stable decision-feedback filtering, IEEE Trans. Circuits Syst. II: Analog and Digital Signal Processing, 40 CAS-II, Jan. 1993. c  1999 by CRC Press LLC pulse shaping filter, the modulator, ... by CRC Press LLC Doherty, J.F. “Channel Equalization as a Regularized Inverse Problem” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca Raton: CRC Press ... in Fig. 31.3 using the eigenvalues of X given by σ 2 i = ( 1 − (i − 1)/10 ) 2 for 1 ≤ i ≤ 10 and σ 2 11 = 0. The RLS algorithm exhibits large dynamic range in the eigenvalue inverse using the matrix...

Ngày tải lên: 22/12/2013, 21:17

... Speech Processing as an Inverse Problem” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca Raton: CRC Press LLC, 1999 c  1999byCRCPressLLC 27 Robust Speech Processing ... Acoust., Speech, Signal Processing, 29, 254–272, April 1981. [7] Boll, S.F., Suppression of acoustic noise in speech using spectral subtraction, IEEE Trans. Acoust., Speech, Signal Processing, 27, ... and Co., Gravenhage, The Nether- lands, 1960. [3] Rabiner, L.R. and Schafer, R.W., Digital Processingof Speech Signals, Prentice-Hall, Englewood Cliffs, NJ, 1978. [4] Atal, B.S., Effectiveness...

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... Systems, 1976. [19] Crochiere, R.E. and Rabiner, L.R., Multirate Digital Signal Processing, Prentice-Hall, Engle- wood Cliffs, NJ, 1983. [20] Malvar, H.S., Signal Processing with Lapped Transforms, Artech House, ... Acoustics, Speech, and Signal Processing, IV,617–620, March 1992. [5] Schuller, G. and Smith, M.J.T., A new framework for modulated perfect reconstruction filter banks, IEEE Trans. Signal Processing, August ... Acoustics, Speech, Signal Processing, 1991. [22] Rothweiler, J., Polyphase quadrature mirror filters—anewsub-band coding technique, Proc. IEEE Intl. Conf. Acoustics, Speech, Signal Processing, 1983. [23]...

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