DIGITAL SIGNAL PROCESSING PPT

Reeves, S.J. “A Survey of Image Processing Software and Image Databases”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC58A Survey of Image ProcessingSoftware and Image DatabasesStanley J. R[r]

Tugnait, J.K. “Validation, Testing, and Noise Modeling”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC16Validation, Testing, and NoiseModelingJitendra K. TugnaitAuburn University16.1 Introduction1[r]

Kosonocky, S. & Xiao, P. “Analog-to-Digital Conversion Architectures”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC5Analog-to-Digital ConversionArchitecturesStephen Kosonock[r]

Bomar, B.W. “Finite Wordlength Effects”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC3Finite Wordlength EffectsBruce W. BomarUniversity of TennesseeSpace Institute3.1 Introduction3.2 Number Repre[r]

Ramachandran, R.P. “Quantization of Discrete Time Signals”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC6Quantization of Discrete TimeSignalsRavi P. RamachandranRowan University6.1 Introduction6.[r]

Feig, E. “Complexity Theory of Transforms in Signal Processing”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC9Complexity Theory of Transformsin Signal ProcessingEphraim FeigI[r]

Yagle, A.E. “Fast Matrix Computations”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC10Fast Matrix ComputationsAndrew E. YagleUniversity of Michigan10.1 Introduction10.2 Divide-and-Conquer Fast Ma[r]

Oppenheim, A.V. & Cuomo, K.M. “Chaotic Signals and Signal Processing”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC71Chaotic Signals and SignalProcessingAlan V. OppenheimMas[r]

Williams, D.B. “Detection: Determining the Number of Sources”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC67Detection: Determining theNumber of SourcesDouglas B. WilliamsGeorgia Institute of Tec[r]

Tzou, K. “Digital Television”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC56Digital TelevisionKou-Hu TzouHyundai Network Systems56.1 Introduction56.2 EDTV/HDTV StandardsMUSE System•HD-MAC[r]

Wornell, G.W. “Fractal Signals”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC73Fractal SignalsGregory W. WornellMassachusetts Institute of Technology73.1 Introduction73.2 Fractal Random Processes[r]

Doherty, J.F. “Channel Equalization as a Regularized Inverse Problem”Digital Signal Processing HandbookEd. Vijay K. Madisetti and Douglas B. WilliamsBoca Raton: CRC Press LLC, 1999c1999byCRCPressLLC31Channel Equalization as aRegularized Inverse ProblemJohn F. DohertyPennsylvani[r]

theevolutionofanonlinearsystemandtheobservationofitsstate,respectively.Thedependenceofthesequencex[n]onitsinitialconditionisemphasizedbywritingx[n]=fn(x[0])wherefn(·)representsthen-foldcompositionoff(·)withitself.Withoutfurtherrestrictionsoftheformoff(·)andg(·),thisclassofsystemsistoolargetoeasilyex[r]

processing literature. Complex representations for signals and the assumption of circularity areparticularly useful in the processingof data or signals froman array of sensors, such asradar antennas.The reader will find them used throughout this chapter of the Handbook.60.2 Complex Envelope Re[r]

,...,τn−1) = csn(τ1,τ2,...,τn−1) +cwn(τ1,τ2,...,τn−1). It is important to note that additivity does not hold for moments.If W(k)is Gaussian representing noise which corrupts the signal of interest, S(k), then by meansof (P2) and (P3), we get that cxn(τ1,τ2

mission, and display.In the broadest meaning of the word, a digital stereoscopic system contains the following compo-nents: stereoscopic camera setup, depth analysis of the digitized and recorded views, compression,transmission or storage, decompression, preprocessing prior to display, and, fi[r]

zen Impuls, der nur aus einem einzi-gen Abtastwert ungleich Null besteht,während alle anderen AbtastwerteNull sind. Die Position und Höhe desPulses kann man über Parameter ein-stellen. Dieses elementare Signal istsehr wichtig und wird bei späterenExperimenten oft benötigt, wie wirnoch sehen w[r]

Hong Wang. “Space-Time Adaptive Processing for Airborne Surveillance Radar.”2000 CRC Press LLC. <http://www.engnetbase.com>.Space-TimeAdaptiveProcessingforAirborneSurveillanceRadarHongWangSyracuseUniversity70.1MainReceiveApertureandAnalogBeamforming70.2DatatobeProcessed70.3ThePr[r]

k= (1−α)X(f ade)kX(f ade)kH.Of course, the two windows could be combined to produce an exponentially faded moving rect-angular window, but this kind of hybrid short memory window has not been the subject of muchstudy in the signal processing literature. Similarly, not much attention[r]

than that corresponding to the noise [11, 14].In a sense, the above examples are both special cases of the following more general situation:EXAMPLE 64.3:Reference SignalIn many systems a reference or pilot signal [19, 20] z(t ) (scalar or vector) is available. If thereference signal is[r]