An introduction to discrete systems
An introduction to discrete systems
Discrete-time signal processing
Discrete-time signal processing
Numerical Analysis: A fast fourier transform algorithm for real-valued series
Communications of the ACM
Digital Signal Processing; Theory, Design, and Implementation
Digital Signal Processing; Theory, Design, and Implementation
Integer squarers with overflow detection
Computers and Electrical Engineering
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Signal processing is a data processing domain that contains a diversity of applications, including speech processing, image processing, radar, sonar, medical imaging, data communications, seismic processing, and many others. Despite the diversity of the applications, this processing domain has a very structured set of characteristics. These include real-time operation, dominance of arithmetic operations, and well-structured data flows. The Real-Time Signal Processor (RSP) is a microprocessor architecture that was created to exploit these characteristics in order to provide an expeditious and economical way to implement signal processing applications. In this paper, the organization and architecture of the RSP are described. Features of the RSP, such as the instruction pipeline and the fractional fixed-point arithmetic, which exploit the characteristics of signal processing to provide additional computational power, are emphasized. Other features, such as the powerful indexing, the saturation arithmetic, the guard bits, and the double-word-width accumulator, which add much to the processor's versatility and programmability, are also highlighted. The performance of the RSP is illustrated through examples.