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1. |
Record Nr. |
UNINA9910454312903321 |
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Autore |
Lebedev L. P |
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Titolo |
The calculus of variations and functional analysis [[electronic resource] ] : with optimal control and applications in mechanics / / Leonid P. Lebedev, Michael J. Cloud |
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Pubbl/distr/stampa |
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Singapore ; ; River Edge, N.J., : World Scientific, c2003 |
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ISBN |
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1-281-93546-8 |
9786611935467 |
981-279-499-9 |
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Descrizione fisica |
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1 online resource (435 p.) |
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Collana |
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Series on stability, vibration, and control of systems. Series A ; ; v. 12 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Functional analysis |
Mechanics |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (p. 415-416) and index. |
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Nota di contenuto |
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Foreword; Preface; Contents; 1. Basic Calculus of Variations; 1.1 Introduction; 1.2 Euler's Equation for the Simplest Problem; 1.3 Some Properties of Extremals of the Simplest Functional; 1.4 Ritz's Method; 1.5 Natural Boundary Conditions; 1.6 Some Extensions to More General Functionals; 1.7 Functionals Depending on Functions in Many Variables; 1.8 A Functional with Integrand Depending on Partial Derivatives of Higher Order; 1.9 The First Variation; 1.10 Isoperimetric Problems; 1.11 General Form of the First Variation; 1.12 Movable Ends of Extremals |
1.13 Weierstrass-Erdmann Conditions and Related Problems1.14 Sufficient Conditions for Minimum; 1.15 Exercises; 2. Elements of Optimal Control Theory; 2.1 A Variational Problem as a Problem of Optimal Control; 2.2 General Problem of Optimal Control; 2.3 Simplest Problem of Optimal Control; 2.4 Fundamental Solution of a Linear Ordinary Differential Equation; 2.5 The Simplest Problem Continued; 2.6 Pontryagin's Maximum Principle for the Simplest Problem; 2.7 Some Mathematical Preliminaries; 2.8 General Terminal Control Problem; 2.9 Pontryagin's Maximum Principle for the Terminal Optimal Problem |
2.10 Generalization of the Terminal Control Problem2.11 Small |
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Variations of Control Function for Terminal Control Problem; 2.12 A Discrete Version of Small Variations of Control Function for Generalized Terminal Control Problem; 2.13 Optimal Time Control Problems; 2.14 Final Remarks on Control Problems; 2.15 Exercises; 3. Functional Analysis; 3.1 A Normed Space as a Metric Space; 3.2 Dimension of a Linear Space and Separability; 3.3 Cauchy Sequences and Banach Spaces; 3.4 The Completion Theorem; 3.5 Contraction Mapping Principle; 3.6 Lp Spaces and the Lebesgue Integral; 3.7 Sobolev Spaces |
3.8 Compactness3.9 Inner Product Spaces Hilbert Spaces; 3.10 Some Energy Spaces in Mechanics; 3.11 Operators and Functional; 3.12 Some Approximation Theory; 3.13 Orthogonal Decomposition of a Hilbert Space and the Riesz Representation Theorem; 3.14 Basis Gram-Schmidt Procedure Fourier Series in Hilbert Space; 3.15 Weak Convergence; 3.16 Adjoint and Self-adjoint Operators; 3.17 Compact Operators; 3.18 Closed Operators; 3.19 Introduction to Spectral Concepts; 3.20 The Fredholm Theory in Hilbert Spaces; 3.21 Exercises; 4. Some Applications in Mechanics |
4.1 Some Problems of Mechanics from the Viewpoint of the Calculus of Variations the Virtual Work Principle; 4.2 Equilibrium Problem for a Clamped Membrane and its Generalized Solution; 4.3 Equilibrium of a Free Membrane; 4.4 Some Other Problems of Equilibrium of Linear Mechanics; 4.5 The Ritz and Bubnov-Galerkin Methods; 4.6 The Hamilton-Ostrogradskij Principle and the Generalized Setup of Dynamical Problems of Classical Mechanics; 4.7 Generalized Setup of Dynamic Problems for a Membrane; 4.8 Other Dynamic Problems of Linear Mechanics; 4.9 The Fourier Method |
4.10 An Eigenfrequency Boundary Value Problem Arising in Linear Mechanics |
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Sommario/riassunto |
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This is a book for those who want to understand the main ideas in the theory of optimal problems. It provides a good introduction to classical topics (under the heading of "the calculus of variations") and more modern topics (under the heading of "optimal control"). It employs the language and terminology of functional analysis to discuss and justify the setup of problems that are of great importance in applications. The book is concise and self-contained, and should be suitable for readers with a standard undergraduate background in engineering mathematics. |
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2. |
Record Nr. |
UNINA9910838288603321 |
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Autore |
Nicosia Giuseppe |
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Titolo |
Machine Learning, Optimization, and Data Science : 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (503 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 14506 |
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Altri autori (Persone) |
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OjhaVarun |
La MalfaEmanuele |
La MalfaGabriele |
PardalosPanos M |
UmetonRenato |
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Disciplina |
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Soggetti |
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Information technology - Management |
Computer networks |
Electronic digital computers - Evaluation |
Computer systems |
Artificial intelligence |
Machine learning |
Computer Application in Administrative Data Processing |
Computer Communication Networks |
System Performance and Evaluation |
Computer System Implementation |
Artificial Intelligence |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Integrated Human-AI Forecasting for Preventive Maintenance Task Duration Estimation -- Exploring Image Transformations with Diffusion |
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Models: A Survey of Applications and Implementation Code -- Geolocation Risk Scores for Credit Scoring Models -- Social Media Analysis: The Relationship between Private Investors and Stock Price -- Deep learning model of two-phase fluid transport through fractured media: a real-world case study -- A Proximal Algorithm for Network Slimming -- Diversity in deep generative models and generative AI -- Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes -- kolopoly: Case Study on Large Action Spaces in Reinforcement Learning -- Alternating mixed-integer programming and neural network training for approximating stochastic two-stage problems -- Heaviest and densest subgraph computation for binary classification. A case study -- SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization -- Accelerated Graph Integration with Approximation of Combining Parameters -- Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non- Visual Environments: A Comparison -- A hybrid steady-state genetic algorithm for the minimum conflict spanning tree problem -- Reinforcement learning for multi-neighborhood local search in combinatorial optimization -- Evaluation of Selected Autoencoders in the Context of End-User Experience Management -- Application of multi-agent reinforcement learning to the dynamic scheduling problem in manufacturing systems -- Solving Mixed Influence Diagrams by Reinforcement Learning -- Multi-Scale Heat Kernel Graph Network for Graph Classification -- Accelerating Random Orthogonal Search for Global Optimization using Crossover -- A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application toVehicles Emissions -- LSTM noise robustness: a case study for heavy vehicles -- Ensemble Clustering for Boundary Detection in High-Dimensional Data -- Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains -- Towards an Interpretable Functional Image-Based Classifier: Dimensionality -- Reduction of High-Density Di use Optical Tomography Data -- On Ensemble Learning for Mental Workload Classification -- Decision-making over compact preference structures -- User-Like Bots for Cognitive Automation: A Survey -- On Channel Selection for EEG-based Mental Workload Classification -- What Song Am I Thinking Of -- Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data -- Sensitivity Analysis for Feature Importance in Predicting Alzheimer?s Disease -- A Radically New Theory of how the Brain Represents and Computes with Probabilities. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning, Optimization, and Data Science, LOD 2023, which took place in Grasmere, UK, in September 2023. The 72 full papers included in this book were carefully reviewed and selected from 119 submissions. The proceedings also contain 9 papers from and the Third Symposium on Artificial Intelligence and Neuroscience, ACAIN 2023. The contributions focus on the state of the art and the latest advances in the integration of machine learning, deep learning, nonlinear optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI. . |
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3. |
Record Nr. |
UNINA9910872882803321 |
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Titolo |
1997 40th Midwest Symposium on Circuits and Systems |
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Pubbl/distr/stampa |
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[Place of publication not identified], : IEEE, 1998 |
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Descrizione fisica |
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1 online resource (2000 pages) |
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Disciplina |
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Soggetti |
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Electric circuits |
Electrical engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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