ABSTRACT
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.