ch1_adcJulie Greenberg

ch1_adcJulie Greenberg - MIT OpenCourseWare...

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Unformatted text preview: MIT OpenCourseWare http://ocw.mit.edu HST.582J / 6.555J / 16.456J Biomedical Signal and Image Processing Spring 2007 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms . (1 HST582J/6.555J/16.456J Biomedical Signal and Image Processing Spring 2007 Chapter 1 - DATA ACQUISITION c Bertrand Delgutte 1999 Introduction The goal of data acquisition is to capture a signal and encode in a form suitable for computer processing with minimum loss of information. Data acquisition typically consists of three stages: transduction, analog conditioning, and analog-to-digital conversion. Transduction is the con- version from one form of energy to another. In present technology, the only form of energy suitable for encoding into a computer is electrical energy, therefore signals need to be converted to analog voltages whose waveforms are ideally the same as those of the original signals. For example, we use a microphone to transduce an acoustic signal, or an electric thermometer to measure temperatures. Transducers are specific to each type of signal, and the study of such devices is beyond the scope of these notes. The second stage of data acquisition, analog signal conditioning, usually consists of amplifying and filtering the analog signal measured with a transducer. Because the purpose of this stage is to provide a good match between the typically low-amplitude, wide-bandwidth transducer signals and the analog-to-digital (A/D) converter, conditioning is best understood after studying A/D conversion. An analog-to-digital converter is a device that transforms a continuous-time signal measured with a transducer into a digital signal that can be represented in a computer. Conceptually, it can be divided into a series of two operations (which are realized simultaneously in actual devices): sampling, in which the continuous-time, analog signal is converted into one that is only defined for discrete times, but whose amplitude can take arbitrary values, and quantization, in which a continuous-amplitude signal is converted into a digital signal that can only take a finite set of values. The sampling operation is particularly critical if we want to avoid loss of information in the conversion. 1.1 Continuous-time and discrete-time signals Many signals are continuous-time in the sense that they are defined at arbitrarily-close points in time. Sine waves are important examples of continuous-time signals because Fourier’s theorem states that most signals of practical interest can be decomposed into an infinite sum of sine waves. A continuous-time sine wave is defined by: x ( t ) = a cos(Ω t + φ ) = a cos(2 πFt + φ ) . 1) where F is the frequency, Ω is the angular frequency, a the amplitude, and φ the phase....
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ch1_adcJulie Greenberg - MIT OpenCourseWare...

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