What is dsp?

In the strict sense of the term, digital signal processing refers to the electronic processing of signals such as sound, radio, and microwaves. In practice, the same characteristics that make Digital Signal Processors (DSPs) good at handling signals make them suitable for many other purposes, such as high-quality graphics processing and engineering simulations. DSPs are essentially fast number-crunchers which also happen to be small, fairly low-cost, and with fairly low-power consumption. Any place you need speed, but could not put a Pentium because it is just too darn big and needs a heat-sink and fan to keep it from melting, is a good candidate for one or more DSPs. Just about any embedded product application that involves rapid numeric processing is a candidate for a DSP.

Note that the acronym DSP can variously mean Digital Signal Processing, the term used for a wide range of techniques for processing signals digitally, or Digital Signal Processor, a specialised type of microprocessor chip. Like a general-purpose microprocessor, a DSP is a programmable device, with its own native instruction code. DSP chips are capable of carrying out millions of floating point operations per second, and like their better-known general-purpose cousins, faster and more powerful versions are continually being introduced. DSPs can also be embedded within complex "system-on-chip" devices, often containing both analog and digital circuitry.

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.