A Central Limit Theorem for Families of Stochastic Processes Indexed by a Small Average Step Size Parameter, and Some Applications to Learning Models

Let θ > 0 be a measure of the average step size of a stochastic process { p n (θ) } n =1 (∞) . Conditions are given under which p n (θ) is approximately normally distributed when n is large and θ is small. This result is applied to a number of learning models where θ is a learning rate parameter...

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Veröffentlicht in:	Psychometrika 1968-12, Vol.33 (4), p.441-449
Hauptverfasser:	Norman, M. Frank, Graham, Norma V.
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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