Representation and Estimation of Cyclostationary Processes
MASSACHUSETTS UNIV AMHERST ENGINEERING RESEARCH INST
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Random signal processes which have been subjected to some form of repetitive operation such a sampling, scanning or multiplexing will usually exhibit statistical properties which vary periodically with time. Systems analysts have tended, for the most part, to treat these cyclostationary processes as though they were stationary. This is done simply by averaging the statistical parameters mean, variance, etc. over one cycle. The first chapter of the report features a detailed historical account of the development and application of cyclostationary processes. The second chapter is an extensive treatment of the topics of transformation, generation, and modelling of cyclostationary processes. The third chapter contains an in-depth treatment of series representations for cyclostationary processes, and their autocorrelation functions, and other periodic kernels. The fourth chapter addresses itself to the problem of least-mean-squared-error linear estimation optimum filtering of cyclostationary processes.