Abstract :
In the real world, noise and noise-like phenomena distort data signals, and the consequence is the occurrence of binary errors. In the laboratory, it is often necessary to mimic the real world, simulating noise, crosstalk, delays, and distortions. In some instances, however, as in testing the performance of error-detecting and error-correcting schemes and codes, it is sufficient to simulate the end result of these phenomena, i.e. to force errors in a data stream in a random, albeit controlled, manner. The authors describe a strategy based on the random Tausworthe generator to achieve this purpose.
