Many engineering signals can be modeled as stationary random processes. The distributions of these signals are defined by covariance functions in the time domain and power spectral densities (PSDs) in the frequency domain. A common problem is to synthesize time series from a random model with desired autospectra, coherence, and phase across multiple signals. For a finite number of randomly sampled signal partitions, the calculated sample PSD does not generally match the distribution PSD. We describe a method for synthesizing waveforms with exactly prescribed auto- and cross-spectral densities. Furthermore, we prove that the random variable induced by the waveform generator is the closest in distribution to the original distribution among all random variables satisfying the PSD constraint. Numerical studies using a Gaussian model demonstrate convergence in practice, and the measured kurtosis and skewness of synthesized waveforms are similar to those obtained by Gaussian sampling. The synthesis method also improves control accuracy in a random vibration control simulation.

Planning the evaluation of an information retrieval system involves two steps: first, a determination of performance descriptors and measures appropriate to the system objectives and, secondly, a development of an evaluation design which ensures the effect of variation in components of interest will be isolated and assessed in an unbiased fashion. This paper examines the question of retrieval system evaluation from the perspective of the user. It presents evaluation procedures which are appropriate to this perspective and which can be used to isolate the effect of variation in the user interface to the system. The general procedure is exemplified by an application to evaluation of an experimental OPAC interface.