Title :
Linear filtering and piecewise linear correlation functions
fDate :
5/1/1969 12:00:00 AM
Abstract :
For a class of piecewise linear correlation functions, it is shown that optimal linear mean-square filtering is achieved with a finite number of samples of the process for any finite observation interval. The class of correlation functions is defined by a particular property of the points at which they change slope. Conditions are discussed under which an arbitrary piecewise linear function is a correlation function. An example demonstrating various aspects of the theory is given, and applications of the theory are considered.
Keywords :
Correlation functions; Filtering; Piecewise-linear approximation; Binary codes; Digital communication; Filtering theory; Information theory; Maximum likelihood detection; Nonlinear filters; Piecewise linear techniques; Propulsion; Pulse compression methods; Viterbi algorithm;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1969.1054306