On the generation of random numbers from heavy-tailed distributions

Article Abstract:

A new, statistically robust technique is developed for the generation of pseudorandom numbers for the design and analysis of robust signal smoothing filters with good smoothing capabilities even when the underlying noise distribution has heavy tails. The method uses a modification of the rejection technique that computes the random variate from a subinterval of a randomly chosen range space. The technique is particularly useful in the performance of a Monte Carlo simulation in the analysis of the smoothing properties of a class of non-linear digital filters. Substantial computation time is saved over conventional random number generation techniques.

Systems analysis, Cost benefit analysis, Product introduction, System Design, Applications, New Technique, Random Number Generation, Filters, technical

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Comments on 'Cumulants: a powerful tool in signal processing.' (response to scientific paper)

Article Abstract:

The solution to stochastic-realization problems developed in previous research does not apply to infinite impulse response systems. An incorrect answer results when an autoregressive moving average model is used for input. An author's reply is included.

Mathematical models, Modeling, Data modeling software, Signal processing, Scientific Research, Stochastic Model

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