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Unformatted text preview: EEC E 151 : Introductio n t o ECE Laborator y Laboratory 2: Introductio n t o Digita l Signa l Processin g an d Communication s Description: Thi s week s exercise s wil l provid e yo u wit h a n introductor y understandin g o f signa l processin g (i n particular , digita l signa l processing , o r DSP ) an d wha t i t i s use d for . Yo u wil l als o b e introduce d t o som e basi c idea s o f digita l communications . Th e la b consist s o f a compute r experimen t wit h a wireles s acousti c modem . Prelab: Read through Sections 1 through 3 and put summary notes in your lab notebook. Ther e i s considerabl e informatio n t o rea d befor e yo u com e int o th e lab , s o b e sur e t o allo t yoursel f enoug h tim e t o full y prepar e fo r th e la b thi s week . You r notebook s wil l b e checke d a t th e beginnin g o f clas s t o ensur e tha t you r prela b ha s bee n completed . Yo u shoul d als o rea d throug h th e remainin g section s t o b e prepare d fo r lab . 1 t Figure 1: An example of an analog, or continuous-time, signal. Introduction Lets begin with some basic definitions. A signal can be thought of as anything that bears infor- mation in which we are interested. Examples include audio signals such as someone honking to get your attention or someone speaking to give you directions, and the light signals at a trac light which indicate if you can proceed through an intersection or need to stop. Signal processing describes the process of manipulating signals to produce some desired result or to gather some information. An analog , or continuous-time signal, can take on any real value at any time t , as illustrated in Fig. 1. Most real-world signals exist only in analog form. A discrete-time signal can only take on values at discrete times, t = kT , where T is a fixed positive real number and k is an integer. A discrete-time version of the analog signal in Fig. 1 is shown in Fig. 2. The discrete-time signal can be obtained by sampling the original analog signal at the discrete time points t = kT , where 1 /T is called the sampling rate. Note that the process of sampling involves discarding an infinite amount of data (i.e., all of the signal values between the sample points). Thus, one would intuitively reason that the original analog signal could not be recovered completely from the discrete-time signal. However, a fundamental result of digital signal processing proved that if the sampling rate is chosen appropriately, then the analog can be recreated exactly from the discrete-time signal. This is key to the modern advances in digital audio and video technologies. The discrete sample points provide a finite set of signal values over a finite time interval (i.e., a fixed number of samples), unlike the analog signal. Thus, it is more suited for processing digitally, i.e., on a computer which uses a fixed (finite) set of numbers by using a fixed number of bits (0s and 1s) to represent data. Since each sample of the discrete-time signal can take on anbits (0s and 1s) to represent data....
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This note was uploaded on 04/18/2008 for the course ECEE 151 taught by Professor Heikenfield during the Fall '08 term at University of Cincinnati.
- Fall '08