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Unformatted text preview: 1 EE 113: Digital Signal Processing Week 1: Introduction 1. Course overview 2. Digital Signal Processing 3. Basic operations & block diagrams 4. Classes of sequences 2 Why should I take this class? f s We study various methods used in analyzing signals and linear systems s These methods are fundamental to engineering design and engineering research s As most of the systems we study are linear, this course paves the way for numerous fields: s Control systems s Communications s Signal processing s Multimedia processing and compression s Etc. etc. s Even other engineers (chemical, mechanical, bioengineering), but also business people etc. use similar tools! 3 Signal examples s In electrical engineering, most signals are voltage signals. s Other signals: images, music etc. 4 Two categories of signals and systems s Continuoustime (EE 102) s Discretetime (EE 113) our concern 5 Continuoustime signals and systems s For a continuoustime signal x ( t ), the independent variable t is continuous. s The dependent variable x , or value of the signal, can also take a continuum of values. 6 Discretetime signals and systems s A discretetime signal x ( nT ) is represented only at discrete values of the independent variable t . s Between these discretetime instants, x may be zero, undefined, or of no interest. These signals are often only represented at uniformly spaced times nT , where n is an integer and T is the sampling interval or sampling period . nT x(nT) 7 Discretetime signals  example s Discretetime signal = sequence s Notation: x(n) n th term of the sequence s Examples: s average daily temperature in LA => the independent variable n specifies the day of interest; the signal measures the average temperature of that day s average monthly temperature in LA 8 Course overview s Digital signal processing : Modifying signals with computers s Web site: http://www.eeweb.ee.ucla.edu s Textbook: Available on the course website are electronic versions of the chapters of An Undergraduate Course on DiscreteTime Signal Processing , by Prof. A.H. Sayed. s Instructor: Mihaela van der Schaar ( mihaela@ee.ucla.edu ) s Introduce TAs 9 Course project s Goal: handson experience with DSP s Practical implementation s Get familiar with MATLAB usage s Interactive system for numerical computation s Extensive signal processing library s Focus on algorithm , not implementation s Work in pairs (2 students) or alone s Brief report s Description on website (posted immediately after midterm) 10 Digital Signal Processing what is it all about?...
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This note was uploaded on 06/01/2010 for the course EE EE113 taught by Professor Mihaela during the Spring '10 term at UCLA.
 Spring '10
 MIHAELA
 Digital Signal Processing, Signal Processing

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