**CHAPTER - 1 Signals, Systems, and Fourier
Transform**

**1.0
INTRODUCTION**

Most signals can be classified into three broad groups ;

1.
**Analog **or **Continuous-Space Signals **: is continuos in both
space and amlitude such as seismic, radar, image, and speech signals

2.
**Discrete-Space Signals** : discrete in space and continuos in
amplitude. A common way to generate such signals is by sampling analog
signals.

**3.
****Digital **or** Discrete Signals** **(sequences)**:
discrete in both space and amlitude. One way in which digital signals are
created is by amplitude quantitization of discrete-space signals.

Digital systems and computers use only digital signals, which are descrete in both space and amplitude. Signal processing concepts based on digital signals requires a detailed treatment of amlitude quantitization, which is extremely difficult and tedious. Most digital signal processing concepts have been developed based on discrete-space signals.Experience shows that theories based on discrete-space signals are often applicable to digital signals.

A system maps an input to an output signal. A major element in studying signal processing is the analysis, design, and implementation of a system that transforms an input signal to a more desirable output signal for a given application. When developing theoretical results about systems, we often impose the constraints of liearity and shift invariance. Altough those constraints are very restrictive, the theoretical results obtained apply in practice at least approximately to many systems.