Self-Adaptive Software for Signal Processing


communication, medical, sonar, radar, equipment health monitoring and many other applications. Frequently, the signal processing system has to meet real-time requirements and provide very large throughput. For example, modern automatic target recognition systems operate with a processing throughput in excess of 10GFLOPS per second. In realtime vibration analysis used for turbine engine testing [1], the aggregate sustained computation rate is also in the GFLOPS range. The high performance requires the use of computing platforms that include the combination of dedicated hardware processors and general-purpose computers, forming a hybrid parallel/distributed configuration. Algorithm complexity, heterogeneity of the computing environment, and real-time operation make the software development for digital signal processing difficult and expensive. Janos Sztipanovits, Gabor Karsai, and Ted Bapty

DOI: 10.1145/274946.274958

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@article{Sztipanovits1998SelfAdaptiveSF, title={Self-Adaptive Software for Signal Processing}, author={Janos Sztipanovits and Gabor Karsai and Ted Bapty}, journal={Commun. ACM}, year={1998}, volume={41}, pages={66-73} }