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Fourth Periodic Monitoring Report on the Status of Implementation Plans in Response to Board-Endorsed IEO Recommendations.

Mathematical optimization. --- Programming (Mathematics)

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Science --- Programming (Mathematics) --- Mathematical models --- Mathematics --- Research --- Information Technology Laboratory (National Institute of Standards and Technology). --- Management

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Kalman filter, particle filter, IMM, PDA, ITS, random sets... The number of useful object-tracking methods is exploding. But how are they related? How do they help track everything from aircraft, missiles and extra-terrestrial objects to people and lymphocyte cells? How can they be adapted to novel applications? Fundamentals of Object Tracking tells you how. Starting with the generic object-tracking problem, it outlines the generic Bayesian solution. It then shows systematically how to formulate the major tracking problems - maneuvering, multiobject, clutter, out-of-sequence sensors - within this Bayesian framework and how to derive the standard tracking solutions. This structured approach makes very complex object-tracking algorithms accessible to the growing number of users working on real-world tracking problems and supports them in designing their own tracking filters under their unique application constraints. The book concludes with a chapter on issues critical to successful implementation of tracking algorithms, such as track initialization and merging.

Operational research. Game theory --- GPS (global positioning system) --- SLP (sequentiele lineaire programmering) --- Bayesian statistics --- Linear programming. --- Programming (Mathematics) --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Operations research --- Production scheduling

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The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).  

Quantitative methods (economics) --- Operational research. Game theory --- Mathematics --- Financial analysis --- toegepaste wiskunde --- stochastische analyse --- financiële analyse --- kansrekening --- Markov processes --- Programming (Mathematics) --- Stochastic control theory --- Finance --- Markov, Processus de --- Programmation (Mathématiques) --- Commande stochastique --- Finances --- Mathematical models --- Modèles mathématiques --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B

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The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).  .

Markov processes. --- Statistical decision. --- Markov processes --- Programming (Mathematics) --- Stochastic control theory --- Finance --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Mathematical models --- Decision problems --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Mathematics. --- Applied mathematics. --- Engineering mathematics. --- Economics, Mathematical. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Quantitative Finance. --- Applications of Mathematics. --- Game theory --- Operations research --- Statistics --- Management science --- Stochastic processes --- Distribution (Probability theory. --- Finance. --- Math --- Science --- Funding --- Funds --- Economics --- Currency question --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Stochastic control theory. --- Mathematical models. --- Economics, Mathematical . --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematical economics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Methodology