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The Computer Journal 1973 16(3):245-253; doi:10.1093/comjnl/16.3.245
© 1973 by British Computer Society
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State estimation algorithms for non-linear stochastic sequential machines

S. G. Tzafestas *

Computer Control Section, Computer Centre, Nuclear Research Centre, ‘Democritus’, Athens, Greece

The problem of estimating the state sequence for a number of stochastic sequential machine models is considered. Basically, all models are assumed to have the structure commonly used in the stochastic control field, i.e. that of a deterministic system corrupted by random disturbances. A Bayesian sequential information processing approach is followed which is most convenient for dealing with finite-state systems. The resulting estimators are given in the form of sequential algorithms which are suitable for a digital computer. However, these estimators can be reduced in the form of finite machines with the aid of well-known state equivalence/reduction techniques. An example is presented which illustrates the effectiveness and usefulness of the theory. The results of the paper are applicable to a large variety of digital communication systems involving noisy channels and also to quantised stochastic control processes.

Received July 1971.

* Computer Control Section, Computer Centre, Nuclear Research Centre, ‘Democritus’, Athens, Greece


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