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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? / We study various methods used in analyzing signals and linear systems These methods are fundamental to engineering design and engineering research As most of the systems we study are linear, this course paves the way for numerous fields: Control systems Communications Signal processing Multimedia processing and compression Etc. etc. Even other engineers (chemical, mechanical, bioengineering), but also business people etc. use similar tools! 3 Signal examples In electrical engineering, most signals are voltage signals. Other signals: images, music etc. 4 Two categories of signals and systems Continuoustime (EE 102) Discretetime (EE 113) our concern 5 Continuoustime signals and systems For a continuoustime signal x ( t ), the independent variable t is continuous. The dependent variable x , or value of the signal, can also take a continuum of values. 6 Discretetime signals and systems A discretetime signal x ( nT ) is represented only at discrete values of the independent variable t . 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 Discretetime signal = sequence Notation: x(n) n th term of the sequence Examples: average daily temperature in LA => the independent variable n specifies the day of interest; the signal measures the average temperature of that day average monthly temperature in LA 8 Course overview Digital signal processing : Modifying signals with computers Web site: http://www.eeweb.ee.ucla.edu 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. Instructor: Mihaela van der Schaar ( mihaela@ee.ucla.edu ) TAs: Martin Andersen and Hyunggon Park 9 Course project Goal: handson experience with DSP Practical implementation Get familiar with MATLAB usage Interactive system for numerical computation Extensive signal processing library Focus on algorithm , not implementation Work in pairs (2 students) or alone Brief report Description on website (posted immediately after midterm) 10 Digital Signal Processing what is it all about?...
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 Spring '08
 Walker
 Digital Signal Processing, Signal Processing

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