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Stochastic Approximation and Its Applications (Hardcover, 2002 ed.)
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Stochastic Approximation and Its Applications (Hardcover, 2002 ed.)
Series: Nonconvex Optimization and Its Applications, 64
Expected to ship within 10 - 15 working days
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Estimating unknown parameters based on observation data conta- ing
information about the parameters is ubiquitous in diverse areas of
both theory and application. For example, in system identification
the unknown system coefficients are estimated on the basis of
input-output data of the control system; in adaptive control
systems the adaptive control gain should be defined based on
observation data in such a way that the gain asymptotically tends
to the optimal one; in blind ch- nel identification the channel
coefficients are estimated using the output data obtained at the
receiver; in signal processing the optimal weighting matrix is
estimated on the basis of observations; in pattern classifi- tion
the parameters specifying the partition hyperplane are searched by
learning, and more examples may be added to this list. All these
parameter estimation problems can be transformed to a root-seeking
problem for an unknown function. To see this, let - note the
observation at time i. e. , the information available about the
unknown parameters at time It can be assumed that the parameter
under estimation denoted by is a root of some unknown function This
is not a restriction, because, for example, may serve as such a
function.
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