The aim of this chapter is to describe the basic characteristics of discrete-time signals, that arise from their continuous-time counterparts, via the application of a sampling process. After the presentation of the basic definitions and illustrative examples, the sampling process is presented in detail and all the involved concepts, such as the aliasing effect, the sampling theorem, the reconstruction of the continuous-time signal from its samples via interpolation, as well as the concept of Nyquist frequency, are described. Then, the notions of the energy and the power for the case of discrete-time signals are defined, and the basic types of such signals, such as the periodic signals, the even and odd signals, and the random and stochastic signals are presented, together with the elementary trigonometric and exponential signals, the step, the impulse and the ramp function for the discrete case, the square and triangular pulses, as well as the sinc function. The basic transformations of discrete-time signals (namely, the time shift, time scaling, and time inversion) are also presented, together with the way in which a discrete-time signal can be combined with the basic signals. The chapter concludes with the presentation of the operations associated with discrete-time signals such as signal addition, multiplication, and convolution, as well as the concepts of cross-correlation and autocorrelation for discrete-time signals.