Abstract
A new representation, called an exponential Fourier density, of a probability density on a circle, S^{1} is introduced. It is shown that a density of bounded variation on S^{1} can be approximated as closely as desired by such a representation in the space of square-integrable functions on S^{1} . The exponential Fourier densities have the desirable feature of being closed under the operation of taking conditional distributions. Facilitated by the use of these densities, finite-dimensional, recursive, and optimal estimation and detection schemes are derived for some simple models including a PSK communication system. A deficiency of the exponential Fourier densities is that they are not closed under convolution. How to circumvent this deficiency is still an open question.
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