From Analog to Digital

Classical DSP applications work with real-world signals, such as sound and radio waves that originate in analog form. Analog means the signals are continuous; they change smoothly from one state to another. Digital computers, on the other hand, treat information discontinuously, as a discrete series of binary numbers. This permits an exactness of measurement and control impossible in analog systems.

The goal of digital signal processing is to use the power of digital computation to manage and modify the signal data. Therefore, the first stage in many DSP systems is to translate smooth real-world signals into a "bumpy" digital approximation. While a sound wave can be depicted as an undulating line, its digital representation looks more like an ascending and descending staircase. This translation is accomplished by an Analog-to-Digital Converter (ADC). In essence, ADCs work like a movie camera, clicking off a series of snapshots that, when strung together, approximate the continuous flow of actual events. The "snapshots" taken by ADCs are actually a series of voltage measurements that trace the rise and fall of the analog signal, like points in a connect-the-dots drawing. If the ADC has done its job well, the data points give a detailed and accurate rendering of the signal.

After a certain amount of clean-up work (to remove extraneous frequencies, among other things), the ADC passes its digitized signal information to a DSP, which does the bulk of the processing. Eventually, when the DSP has finished its chores, the digital data may be turned back into an analog signal, albeit one that is quite different from and much improved over the original. For instance, a DSP can filter the noise from a signal, remove unwanted interference, amplify certain frequencies and suppress others, encrypt information, or analyze a complex wave form into its spectral components. In plainer language, DSPs can clean the crackle and hiss from music recordings, remove the echo from communications lines, make internal organs stand out more clearly in medical CAT scans, scramble cellular phone conversations to protect privacy, and assess seismic data to pinpoint new oil reserves.

Of course there are also DSP applications that don't require Analog-to-Digital translation. The data is digital from the start, and can be manipulated directly by the DSP. An example of this is computer graphics where DSPs create mathematical models of things like weather systems, images and scientific simulations.

Date: 2015-02-03; view: 913