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Factorization Methods for Discrete Sequential Estimation

This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing;

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Sequential Estimation

This book devoted to sequential estimation presents the advances of the past fifteen years including those in the areas of three--stage;

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An Operator Perspective on Signals and Systems

In this monograph, we combine operator techniques with state space methods to solve factorization, spectral estimation, and interpolation;

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Optimal Filtering

communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to;

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Sequential Methods and Their Applications

tests. It then presents numerous multistage estimation methods for fixed-width confidence interval as well as minimum and bounded risk problems;

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Fast Sequential Monte Carlo Methods for Counting and Optimization

for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for;

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Digital Spectral Analysis with Applications

Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their implementation. Coverage includes spectral;

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Cognitive Fusion for Target Tracking

enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation;

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Applied Sequential Methodologies

real world, Applied Sequential Methodologies communicates invaluable techniques for data mining, agricultural science, genetics, computer;

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Combinatorial Methods in Discrete Distributions

distributions of independent random occupancy numbers, and provides excellent studies of occupancy and sequential occupancy distributions, convolutions;

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Guide to Graph Algorithms

comparative analysis of sequential, parallel and distributed graph algorithms - including algorithms for big data - and an investigation into the;

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Statistical Methods for Recommender Systems

challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling;

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Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filtering

of sequential state estimation in linear, Gaussian dynamic models, which corresponds to the well-known Kalman (or Kalman-Bucy) filter. Finally, we move;

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Particle Filters for Random Set Models

This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and;

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Discrete Inverse and State Estimation Problems

of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for;

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Discrete Inverse and State Estimation Problems

of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for;

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Audio Source Separation

based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source;

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Optimal and Robust Estimation

estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic;

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Iterative Incomplete Factorization Methods

This book is devoted to numerical methods for solving sparse linear algebra systems of very large dimension which arise in the;

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Group Sequential and Confirmatory Adaptive Designs in Clinical Trials

estimation methods and methods for the determination of an overall p-value. Part I of the book provides the group sequential methods that are;

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Theory Of Preliminary Test And Stein-Type Estimation With Applications

of estimation in a variety of standard models used in applied statistical inference. It is an in-depth introduction to the estimation theory for;

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Subspace Methods for System Identification

realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included;

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An Introduction to Sequential Monte Carlo

become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population;

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Introduction to Process Control

This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the;

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Quantum Computational Number Theory

, elliptic curve arithmetic, conjecture and numerical verification. The author discusses quantum algorithms for solving the Integer Factorization;

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Optimal Estimation of Dynamic Systems

sequential state estimation, and additional examples and exercises. An ideal self-study guide for practicing engineers as well as senior;

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Nonlinear Estimation

sample point filters (also called Gaussian filters) and their variants for nonlinear estimation problems, for which no closed-form solution;

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