数字信号处理汇总.docVIP

Understanding Digital Signal Processing: Periodic Sampling By Richard G. Lyons Dec 3, 2004 Sample Chapter is provided courtesy of Prentice Hall Professional Periodic sampling, the process of representing a continuous signal with a sequence of discrete data values, pervades the field of digital signal processing. This chapter covers that process in detail, and how you can use it in your business. Periodic sampling, the process of representing a continuous signal with a sequence of discrete data values, pervades the field of digital signal processing. In practice, sampling is performed by applying a continuous signal to an analog-to-digital (A/D) converter whose output is a series of digital values. Because sampling theory plays an important role in determining the accuracy and feasibility of any digital signal processing scheme, we need a solid appreciation for the often misunderstood effects of periodic sampling. With regard to sampling, the primary concern is just how fast a given continuous signal must be sampled in order to preserve its information content. We can sample a continuous signal at any sample rate we wish, and well get a series of discrete values—but the question is, how well do these values represent the original signal? Lets learn the answer to that question and, in doing so, explore the various sampling techniques used in digital signal processing. 2.1 ALIASING: SIGNAL AMBIGUITY IN THE FREQUENCY DOMAIN There is a frequency-domain ambiguity associated with discrete-time signal samples that does not exist in the continuous signal world, and we can appreciate the effects of this uncertainty by understanding the sampled nature of discrete data. By way of example, suppose you were given the following sequence of values, and were told that they represent instantaneous values of a time-domain sinewave taken at periodic intervals. Next, you were asked to draw that sinewave. Youd start by plotting the sequence of values shown by the dots in Figure 2-1(a)