Adaptive Algorithms and Stochastic Approximations pp 343-347 | Cite as
Appendix to Part II
Chapter
Abstract
This section was principally intended to provide course support. It was meant to be self-contained and all technical difficulties were to be eliminated through over-realistic assumptions. In fact, the particular instance which we shall describe has already been seen in substance in Example 4 of Subsection 1.1.2 (cf. also 1.1.4), and studied in particular in Subsection 1.10.1. Here once again is the algorithm with its assumptions.
$${\theta_{{n + 1}}} = {\theta_n} + {\gamma_{{n + 1}}}H\left( {{\theta_n},\,{X_{{n + 1}}}} \right)$$
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© Springer-Verlag Berlin Heidelberg 1990