series of numbers can then be transmitted to a remote location in discrete form using digital 10:00 12:00 14:00 16:00 18:00 20:00 22:00 24:00 Figure 5.3 Temperature graph for Adelaide Table 5.1 The temperature table - sampled every hour 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 24:00 Temperature (C) Table 5.2 The temperature table - sampled every 2 h 10:00 12:00 14:00 16:00 18:00 20:00 22:00 24:00 Temperature (C) From Analogue to Digital telecommunications technologies. For example, the temperature graph in Figure 5.3 can be shown as a set of numbers corresponding to regular measurements every half an hour. This is shown in Table 5.1. The process of measurement at regular intervals is known as sam- pling, and the frequency of sampling, in this case once every hour, is known as the sampling rate or sampling frequency. The same temperature graph may be represented as a set of discrete numbers corresponding to measurements every 2 h, and demonstrated in Table 5.2. It can be argued that the two representations are quite equal in the information they convey. However, if both representations as shown in Table 5.1 and Table 5.2 are equivalent, then obvi- ously Table 5.2 is more efficient as it needs fewer data points to convey the same temperature information. It is therefore important to determine the necessary sampling frequency for rep- resenting a particular analogue signal to ensure that all information is preserved efficiently. Another example shown in Figure 5.4 is of a voice clip. The amplitude of human voice is an analogue, continuous waveform. Such a waveform may also be sampled at regular intervals and represented as a series of discrete numbers. The representation of an analogue signal using a discrete set of numbers is known as digital representation; and the process as analogue to digital conversion (A to D in short). The reverse process is known as digital to analogue conversion (D to A). As noted above, sampling frequency needs to be sufficiently fast to accurate