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• Print publication year: 2003
• Online publication date: June 2012

15 - Sampling of continuous-time signals

Summary

INTRODUCTION

In chapter 1 signals were divided into continuous-time and discrete-time signals. Ever since, we have almost exclusively discussed continuous-time signals. This chapter, being the first chapter of part 5, can be considered as sort of a transition from the continuous-time to the discrete-time signals. In section 15.1 we first introduce a number of important discrete-time signals, which are very similar to well-known continuous-time signals like the unit pulse or delta function. Subsequently, we pay special attention in section 15.2 to the transformation of a continuous-time signal into a discrete-time signal (sampling) and vice versa (reconstruction), leading to the formulation and the proof of the so-called sampling theorem in section 15.3. The sampling theorem gives a lower bound (the so-called Nyquist frequency) for the sampling frequency such that a given continuous-time signal can be transformed into a discrete-time signal without loss of information. We close with the treatment of the so-called aliasing problem in section 15.4. This problem arises when a continuous-time signal is transformed into a discrete-time signal using a sampling frequency which is too low.

LEARNING OBJECTIVES

After studying this chapter it is expected that you

- can describe discrete-time signals using unit pulses

- can describe periodic discrete-time signals using periodic unit pulses

- can explain the meaning of the terms sampling, sampling period and sampling frequency

- can explain the sampling theorem and can apply it

- can understand the reconstruction formula for band-limited signals

- can describe the consequences of the aliasing problem.