Resumen
Digital signal processing systems are widely used in 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 10 GFLOPS per second. In real-time vibration analysis used for turbine engine testing, 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. Structurally adaptive systems can address problems related to fault-tolerance, robust behavior and the need for dynamic system architectures. It is shown how to implement an adaptive system for a large-scale DSP application the CADDMAS turbine engine analysis system-where operational circumstances demand changes in structure during operation.