... Hampshire);Kenneth H. Jacker, (Department of Computer Science, Appalachian StateUniversity); Rajiv Kapadia, Ph.D. (Department of Electrical Engineering, MankatoState University); Dan King (Analog ... 11Mean and Standard Deviation 13 Signal vs. Underlying Process 17The Histogram, Pmf and Pdf 19The Normal Distribution 26 Digital Noise Generation 29Precision and Accuracy 32Chapter 3. ADC and ... electrical engineering, to namejust a few. The goal is to present practical techniques while avoiding the barriers ofdetailed mathematics and abstract theory. To achieve this goal, three strategies...
... considered a bandlimited signal. It is this signal thatis sampled and converted toa discrete-time signal and coded toadigital signal by the analog -to- digital converter (ADC) that was briefly ... data on a few ADCs currently available are given in Table 1.3 [3].Hence digitalsignalprocessing is restricted to approximately one megahertz,and analog signal processors are necessary for processing ... processing signals above thatfrequency, for example, processing of radar signals. In such applications, analog signal processing is a more attractive and viable choice, and currently a lot ofresearch...
... international normalized ratio (INR), and a liver panel. Although the serum aminotransferase level correlates poorly with liver histology, the ratio of aspartate aminotransferase (AST) to alanine ... HCC, and mortality. In addition, HCV infection has been linked toa variety of extra-hepatic manifestations such as autoimmune diseases, lymphoma, monoclonal gammopathies and cryoglobulinemia. ... International Publisher. All rights reserved Review A PracticalApproachto Managing Patients with HCV Infection Richard H. Huang, and Ke-Qin Hu Division of Gastroenterology and Hepatology,...
... quantitation and three approved drugs for HBV treatment, and presents an updated and practical clinical approachto managing CHB. Highly sensitive PCR-based quantitation of HBV DNA makes it ... normal transaminases. ALT Levels For many years, ALT has been used as a standard surrogate for the activity of CHB. Thus, ALT level in combination with HBV DNA level and histological activity ... treatment. Overall, LAM and ADV are probably more favorable due to convenient administration, better tolerance, and less cost. When planning a LAM treatment, medical adherence and regular follow-up...
... fetal monitoring, patient moni-toring, and ECG and EEC mapping. Another example of advanced digital signal processing is found in hearing aids and cardiac pacemakers.5. Image Processing. Image ... restricted to approximately one megahertz,and analog signal processors are necessary for processing signals above thatfrequency, for example, processing of radar signals. In such applications, analog signal ... decreases and therefore the accuracy and dynamicrange of the input and output data decrease.For example, data on a few ADCs currently available are given in Table 1.3 [3].Hence digitalsignal processing...
... Space-TimeAdaptiveProcessingforAirborneSurveillanceRadarHongWangSyracuseUniversity70.1MainReceiveApertureandAnalogBeamforming70.2DatatobeProcessed70.3TheProcessingNeedsandMajorIssues70.4TemporalDOFReduction70.5AdaptiveFilteringwithNeededandSample-SupportableDOFandEmbeddedCFARProcessing70.6Scan -To- ScanTrack-Before-DetectProcessing70.7Real-TimeNonhomogeneityDetectionandSampleConditioningandSelection70.8SpaceorSpace-RangeAdaptivePre-SuppressionofJammers70.9ASTAPExamplewithaRevisittoAnalogBeamforming70.10SummaryReferencesSpace-TimeAdaptiveProcessing(STAP)isamulti-dimensionalfilteringtechniquedevelopedforminimizingtheeffectsofvariouskindsofinterferenceontargetdetectionwithapulsedairbornesurveillanceradar.Themostcommondimensions,orfilteringdomains,generallyincludetheaz-imuthangle,elevationangle,polarizationangle,dopplerfrequency,etc.inwhichtherelativelyweaktargetsignaltobedetectedandtheinterferencehavecertaindifferences.Inthefollowing,theSTAPprinciplewillbeillustratedforfilteringinthejointazimuthangle(space)anddopplerfrequency(time)domainonly.STAPhasbeenaveryactiveresearchanddevelopmentareasincethepublicationofReedetal.’sseminalpaper[1].WiththerecentlycompletedMultichannelAirborneRadarMeasurementproject(MCARM)[2]–[5],STAPhasbeenestablishedasavaluablealternativetothetraditionalapproaches,suchasultra-lowsidelobebeamformingandDisplacedPhaseCenterAntenna(DPCA)[6].MuchofSTAPresearchanddevelopmenteffortshavebeendrivenbytheneedstomakethesystemaffordable,tosimplifyitsfront-hardwarecalibration,andtominimizethesystem’sperformancelossinseverelynonhomogeneousenvironments.Figure70.1isageneralconfigurationofSTAPfunctionalblocks[5,7]whoseprincipleswillbediscussedinthefollowingsections.c1999byCRCPressLLC ... spatialdomain.Channel calibration is a problem issue for many STAP approaches. In order to minimize perfor-mancedegradation, thechannelswithsome STAPapproachesmustbematchedacrossthesignalband,and ... Kelly, E.J., An adaptive detection algorithm,IEEE Trans. on Aerospace and Electronic Systems,AES-22(1), 115–127, March 1986.[23] Kazakos, D. and Papantoni-Kazakos, P.,Detection and Estimation,Computer...
... and delay estimation (JADE)for multipath signals arriving at an antenna array,IEEE Comm. Lett.,Jan. 1997.[50] Van Veen, B.D. and Buckley, K. M., Beamforming: a versatile approachto spatial filtering,IEEEASSP ... IntroductionandMotivationThischapterreviewstheapplicationsofantennaarraysignalprocessingtomobilenetworks.Cellularnetworksarerapidlygrowingaroundtheworldandanumberofemergingtechnologiesareseentobecriticaltotheirimprovedeconomicsandperformance.Amongtheseistheuseofmultipleantennasandspatialsignalprocessingatthebasestation.ThistechnologyisreferredtoasSmartAntennasor,moreaccurately,asSpace-TimeProcessing(STP).STPreferstoprocessingtheantennaoutputsinbothspaceandtimetomaximizesignalquality.Acellulararchitectureisusedinanumberofmobile/portablecommunicationsapplications.Cellsizesmayrangefromlargemacrocells,whichservehighspeedmobiles,tosmallermicrocellsorverysmallpicocells,whicharedesignedforoutdoorandindoorapplications.Eachoftheseoffersdifferentchannelcharacteristicsand,therefore,posesdifferentchallengesforSTP.Likewise,differentservicedeliverygoalssuchasgradeofserviceandtypeofservice:voice,data,orvideo,alsoneedspecicSTPsolutions.STPprovidesthreeprocessingleverages.Therstisarraygain.Multipleantennascapturemoresignalenergy,whichcanbecombinedtoimprovethesignal -to- noiseratio(SNR).Nextisspatialdiversitytocombatspace-selectivefading.Finally,STPcanreduceco-channel,adjacentchannel,andinter-symbolinterference.Theorganizationofthischapterisasfollows.InSection68.2,wedescribethevectorchannelmodelforabasestationantennaarray.InSection68.3wediscussthealgorithmsforSTP.Section68.4outlinestheapplicationsofSTPincellularnetworks.Finally,weconcludewithasummaryinSection68.5.c1999byCRCPressLLC ... M. and Paulraj, A. , Blind separation of synchronous co-channel digital signals using an antenna array. Part I. Algorithms,IEEE Trans. on Signal Processing, 44(5),1184–1197, May 1996.[44] Tong,...
... perturbation-based, and neural network-based methodsare classified as adaptive because on average they move towards an EVD at each update. On the otherhand, rank one, rank k, and sphericalized ... scheme.66.3.3 Forward-Backward AveragingIn manysubspace tracking problems, forward-backward (FB) averaging can improve subspaceas wellas DOA (or frequency) estimation performance. Although FB averaging ... projection approximation subspace tracker (PAST) which tracks an arbitrary basis forthe signal subspace, and PASTd which uses deflation to track the individual eigencomponents. A multi-vector eigen tracker...
... Regalia, P .A. ,Adaptive IIR Filtering in SignalProcessing and Control,Marcel-Dekker, NewYork, 1995.[20] Ren,W. andKumar, P.R., Stochasticparallelmodel adaptation: theoryand applicationstoactivenoise ... between these twocategories is the Steiglitz-McBride approach toadaptiveIIR filtering.Each of these approaches has certain advantages but also disadvantages. We have evaluated eachapproachin termsofconvergence ... of large deviations ofthealgorithms fromaminimum point becomeslargewith time with constantà. As apractical matter,however, one can expect the parameter vector toapproach and stay near a minimizing...
... 1982–1989, Aug. 1996.[19] Sayed, A. H. and Kailath, T., A state-space approachto adaptive RLS filtering,IEEE Signal Processing Magazine, 11(3), 18–60, July 1994.The time-domain feedback and small gain ... B., Sayed, A. H., and Kailath, T., Linear estimation in Krein spaces — Part II: Applica-tions,IEEE Trans. Automatic Control, 41(1), 34–49, Jan. 1996.The small gain analysis is a standard tool ... in adaptive filtering and H∞estimation and control can be foundin[14] Hassibi, B., Sayed, A. H., and Kailath, T., LMS and backpropagation are minimax filters, inNeural Computation and Learning,...
... not guaranteed to be independent fromsample to sample. Even so,numerous analyses and simulations have indicatedthat theseassumptionslead toa reasonably accurate characterization of the behavior ... straightforward, simulation has two drawbacks that make it a poor sole choice for charac-terizing the behavior of an adaptive lter:ã Selecting design parameters via simulation alone is an iterative ... systemsassimpleas the LMS adaptive lter.ã The amount of data needed to accurately characterize the behavior of the adaptive filter forall cases of interest may be large. If real-world signal measurements...
... ARMA model has an advantage over the AR and MA models because it can better fit spectrawith nulls and peaks. Its disadvantage is that it is more difficult to estimate its parameters than theparameters ... from vectors that lie in the signal subspace. The main idea there is to form a reducedrankautocorrelation matrix which is an estimate of the signal autocorrelation matrix. Since this estimateis ... here are wide-sense stationary. The stationarity assumption,however, is often a mathematical abstraction and only an approximation in practice. Many physicalprocesses are actually nonstationary...
... Gainsã Signal Detection:Single Signal 13.6 Spatio-Temporal SignalsDetection: Known Gains and Known Spatial CovarianceãDetection: Unknown Gains andUnknown SpatialCovariance13.7 Signal ClassicationClassifying ... Classification13.4 The Linear Multivariate Gaussian Model13.5 Temporal Signals in Gaussian Noise Signal Detection: Known Gainsã Signal Detection: UnknownGainsã Signal Detection: Random Gainsã Signal ... normal withzero mean and p ì p covariance matrix Rsthe compound signal component sc= Bs is an n-dimensional random Gaussian vector with zero mean and rank p covariance matrix BRsBH .A standard...