This monograph presents a unified mathematical framework for a wide range of problems in estimation and control. The authors discuss the two most commonly used methodologies: the stochastic H² approach and the deterministic (worst-case) H [infinity] approach. Despite the fundamental differences in the philosophies of these two approaches, the authors have discovered that, if indefinite metric spaces are considered, they can be treated in the same way and are essentially the same. The benefits and consequences of this unification are pursued in detail, with discussions of how to generalize well-known results from H² theory to H [infinity] setting, as well as new results and insight, the development of new algorithms, and applications to adaptive signal processing. The authors deliberately have placed primary emphasis on estimation problems which enable one to solve all the relevant control problems in detail. They also deal mostly with discrete-time systems, since these are the ones most important in current applications.
Given k populations, it is often desirable to select the best t. The body of ranking and selection literature from 1954 to 1992 thoroughly addressed this problem for small k...
This book was written as the result of a study undertaken to establish the interaction of these three components over as large a range as possible. Originally published in 1972.
This book synthesizes those techniques from numerical analysis, algorithms, data structures, and optimization theory mostcommonly employed in statistics and machine learning.
本书是一部经典的有关统计信号处理的权威著作.全书分为两卷, 分别讲解了统计信号处理基础的估计理论和检测理论.卷I详细介绍了经典估计理论和贝叶斯估计, 总结了各种估计方法, ...
Empirical Process Techniques for Dependent Data
Vou Vol Vo B ( t ) ( 1.5 ) 0 V012 ( a ) V021 W Vo2 V022 = i 11/2 1/2 ( c ) V1 1/2 + Wy Vø1 Vø2 = B ( 1 ) – B ( 1/2 ) = Vø / 2 – Wo - - V V ( b ) FIG 2. ( a ) Binary tree for interpolation of Brownian motion , B ( t ) .
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for ...
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for ...
Introduction To Statistical Signal Processing With Applications,1/e