Filtering and System Identification: A Least Squares Approach

Chapter 3: Discrete-Time Signals and Systems

Overview

After studying this chapter you will be able to

  • define discrete-time and continuous-time signals;

  • measure the size of a discrete-time signal using norms;

  • use the z-transform to convert discrete-time signals to the complex z-plane;

  • use the discrete-time Fourier transform to convert discrete-time signals to the frequency domain;

  • describe the properties of the z-transform and the discrete-time Fourier transform;

  • define a discrete-time state-space system;

  • determine properties of discrete-time systems such as stability, controllability, observability, time invariance, and linearity;

  • approximate a nonlinear system in the neighborhood of a certain operating point by a linear time-invariant system;

  • check stability, controllability, and observability for linear timeinvariant systems;

  • represent linear time-invariant systems in different ways; and

  • deal with interactions between linear time-invariant systems.

3.1 Introduction

This chapter deals with two important topics: signals and systems. A signal is basically a value that changes over time. For example, the outside temperature as a function of the time of the day is a signal. More specifically, this is a continuous-time signal; the signal value is defined at every time instant. If we are interested in measuring the outside temperature, we will seldom do this continuously. A more practical approach is to measure the temperature only at certain time instants, for example every minute. The signal that is obtained in that way is a sequence of numbers; its values correspond to certain time instants. Such an ordered sequence is called a discrete-time...

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