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Nonlinear Stochastic Systems with Incomplete Information - Filtering and Control (Hardcover, 2013 ed.)
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Nonlinear Stochastic Systems with Incomplete Information - Filtering and Control (Hardcover, 2013 ed.)
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Nonlinear Stochastic Processes addresses the frequently-encountered
problem of incomplete information. The causes of this problem
considered here include: missing measurements; sensor delays and
saturation; quantization effects; and signal sampling. Divided into
three parts, the text begins with a focus on H filtering and
control problems associated with general classes of nonlinear
stochastic discrete-time systems. Filtering problems are considered
in the second part, and in the third the theory and techniques
previously developed are applied to the solution of issues arising
in complex networks with the design of sampled-data-based
controllers and filters. Among its highlights, the text provides: *
a unified framework for filtering and control problems in complex
communication networks with limited bandwidth; * new concepts such
as random sensor and signal saturations for more realistic
modeling; and * demonstration of the use of techniques such as the
Hamilton-Jacobi-Isaacs, difference linear matrix, and
parameter-dependent matrix inequalities and sums of squares to
handle the computational challenges inherent in these systems. The
collection of recent research results presented in Nonlinear
Stochastic Processes will be of interest to academic researchers in
control and signal processing. Graduate students working with
communication networks with lossy information and control of
stochastic systems will also benefit from reading the book.
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