Digital signal processing (DSP) is used in numerous applications. These applications include telephony, mobile radio, satellite communications, speech processing, video and image processing, biomedical applications, radar, and sonar. Real-time implementations of DSP systems require design of hardware that can match the application sample rate to the hardware processing rate (which is related to the clock rate and the implementation style). Thus, real-time does not always mean high speed. Real-time architectures are capable of processing samples as they are received from the signal source, as opposed to storing them in buffers for later processing as done in batch processing. Furthermore, real-time architectures operate on an infinite time series (since the number of the samples of the signal source is so large that it can be considered infinite). While speech and sonar applications require lower sample rates, radar and video image processing applications require much higher sample rates. The sample rate information alone cannot be used to choose the architecture. The algorithm complexity is also an important consideration. For example, a very complex and computationally intensive algorithm for a low-sample-rate application and a computationally simple algorithm for a high-sample-rate application may require similar hardware speed and complexity. These ranges of algorithms and applications motivate us to study a wide variety of architecture styles.
|Original language||English (US)|
|Title of host publication||Circuits, Signals, and Speech and Image Processing|
|State||Published - Jan 1 2006|