PPT-Chapter 1 -Discrete Signals

  A Sampled or discrete time signal xn is just an ordered sequence of values corresponding to the index n that embodies the time history of the signal A discrete signal is represented by a sequence of values xn 12. ransform tak es the form of olynomial Enables in terpretation of the signal in terms of the ro ots of the olynomial corresp onds to dela of one unit in the signal The ransform of discrete time signal is de57356ned as 573441 z 1 where e brPage 2br Th 5.1 Discrete-time Fourier Transform . Representation for discrete-time signals. Chapters 3, 4, 5. Chap. 3 . Periodic. Fourier Series. Chap. 4 . Aperiodic . Fourier Transform . Chap. 5 . Aperiodic . and its discrete version is explained in Section VI-B. Fast 2- By definition, the functions r/?(x) and G(Z) can be consid- D wavelet algorithms are given in Appendix D. Section VII ered to be wavelets Examples of signals:. Voltage output of a RLC circuit, stock market, ECG, speech, sequences of bases in a gene, MRI or CT scan. Examples of systems:. RLC circuit, an algorithm for predicting future of stock market, an algorithm for detecting abnormal heart rhythms, speech understanding systems, edge detection algorithm for medical images.. 5.1 Discrete-time Fourier Transform . Representation for discrete-time signals. Chapters 3, 4, 5. Chap. 3 . Periodic. Fourier Series. Chap. 4 . Aperiodic . Fourier Transform . Chap. 5 . Aperiodic . Example. The representation of discrete-time signals in terms of impulse. Convolution. The representation of continuous-time signals in terms of impulse. Properties of LIT systems. Commutative property.  . A Sampled or discrete time signal x[n] is just an ordered sequence of values corresponding to the index n that embodies the time history of the signal. A discrete signal is represented by a sequence of values x[n] ={1,2,. Nyquist. Theorem . Richa. Sharma. Dept. of Physics And Astrophysics. University of Delhi. Signal : . Any physical quantity that varies with time, space, or any other independent variable or variables.. Instructor: . Dr. Ghazi Al Sukkar. Dept. of Electrical Engineering. The . University of Jordan. Email: . ghazi.alsukkar@ju.edu.jo. 1. Fall 2014. 2. Course Details. Objective. Establish a background in Signal and System Analysis. NAGERCOIL.. COURSE ON DIGITAL SIGNAL PROCESSING. Course Objectives. Design FIR and IIR filters by hand to meet specific magnitude and phase requirements.. Perform Z and inverse Z transforms using the definitions, Tables of Standard Transforms and Properties, and Partial Fraction Expansion.. Chapter 5. Discrete-Time Process Models. Discrete-Time Transfer Functions. The input to the continuous-time system . G. (. s. ) is the signal:. The system response is given by the convolution integral:. Chapter 5. Discrete-Time Process Models. Discrete-Time Transfer Functions. The input to the continuous-time system . G. (. s. ) is the signal:. The system response is given by the convolution integral:. 3233 Pagosa Ct., El Paso, TX 79904 Phone (915) 751 - 3222 FAX (915) 751 - 3222 Z eli Systems SATPAK - CPCI - MGUE - FORCE5M Features:  The SATPAK - CPCI - MGUE - FORCE5M is a 6U form factor carr Chapter-2 : Signals & Systems . Review. Marc Moonen & . Toon. van . Waterschoot. Dept. E.E./ESAT-STADIUS, KU Leuven. marc.moonen@kuleuven.be. www.esat.kuleuven.be. /. stadius. /. Chapter-2 : Signals & Systems Review.