Titlebook: Stochastic Lagrangian Adaptation; David Levanony,Peter E. Caines Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusiv

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Introduction,rement may be abandoned when certain control-biased estimation methods are utilized. One such methodology is realized in this work which is built upon a geometric study of limit sets of parameter estimates which give rise to closed-loop indistinguishable dynamics.

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2191-8198 stinguishing the work from standard analyses. The work is ba.This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimation algorithm is engineered to drive

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Book 2024epresenting the true closed-loop dynamics. By incorporating a performance monitoring feature, this approach ensures that the estimate converges to the true system parameters. Concurrently, it delivers optimal long-term LQ closed-loop performance. This groundbreaking work offers a significant advancement in the field of stochastic control systems..

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Heuristic Approaches for a TSP Variant: The Automatic Meter Reading Shortest Tour Problemstering-based algorithm and a convex hull-based algorithm, are proposed to find near-optimal feasible solutions. The algorithms are tested on various datasets, and the numerical results show that both heuristic algorithms perform effectively and efficiently.

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ogress being made by Italian researchers and is of great value to anyone interested in all fields of veterinary science, both theoretical and applied, ranging from animal health and care to animal production and food hygiene.978-3-642-44269-8978-3-642-36488-4