Книги: "Algorithm stability"

1

Graham, Ronald E. Linearization of digital derived rate algorithm for use in linear stability analysis. [Washington, DC?]: National Aeronautics and Space Administration, 1985.

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2

Orlik, Lyubov', and Galina Zhukova. Operator equation and related questions of stability of differential equations. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1061676.

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The monograph is devoted to the application of methods of functional analysis to the problems of qualitative theory of differential equations. Describes an algorithm to bring the differential boundary value problem to an operator equation. The research of solutions to operator equations of special kind in the spaces polutoratonny with a cone, where the limitations of the elements of these spaces is understood as the comparability them with a fixed scale element of exponential type. Found representations of the solutions of operator equations in the form of contour integrals, theorems of existence and uniqueness of such solutions. The spectral criteria for boundedness of solutions of operator equations and, as a consequence, sufficient spectral features boundedness of solutions of differential and differential-difference equations in Banach space. The results obtained for operator equations with operators and work of Volterra operators, allowed to extend to some systems of partial differential equations known spectral stability criteria for solutions of A. M. Lyapunov and also to generalize theorems on the exponential characteristic. The results of the monograph may be useful in the study of linear mechanical and electrical systems, in problems of diffraction of electromagnetic waves, theory of automatic control, etc. It is intended for researchers, graduate students functional analysis and its applications to operator and differential equations.

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3

Higham, Nicholas J. Accuracy and stability of numerical algorithms. Philadelphia: SIAM, 1996.

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4

Higham, Nicholas J. Accuracy and stability of numerical algorithms. 2nd ed. Philadelphia, PA: Society for Industrial & Applied Math, 2003.

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5

Higham, Nicholas J. Accuracy and stability of numerical algorithms. Philadelphia: Society for Industrial and Applied Mathematics, 1996.

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6

Higham, Nicholas J. Accuracy and stability of numerical algorithms. 2nd ed. Philadelphia: Society for Industrial and Applied Mathematics, 2002.

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7

Solo, Victor. Adaptive signal processing algorithms: Stability and performance. Englewood Cliffs, N.J: Prentice Hall, 1995.

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8

Zhang, Huaguang. Adaptive Dynamic Programming for Control: Algorithms and Stability. London: Springer London, 2013.

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9

Wen, Wu. Verifying stability of dynamic soft-computing systems. [Washington, DC]: National Aeronautics and Space Administration, 1997.

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10

Wen, Wu. Verifying stability of dynamic soft-computing systems. [Washington, DC]: National Aeronautics and Space Administration, 1997.

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11

1963-, Zakhor Avideh, ed. Sigma Delta modulators: Nonlinear decoding algorithms and stability analysis. Boston: Kluwer Academic Publishers, 1993.

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12

Hein, Søren. Sigma Delta Modulators: Nonlinear Decoding Algorithms and Stability Analysis. Boston, MA: Springer US, 1993.

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13

Lobo, M. Stability theorems concerning high order explicit algorithms for the linear advection equation. Cranfield, Eng: College of Aeronautics, Cranfield Institute of Technology, 1985.

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14

P, Banks Stephen. Can Perceptrons find Lyapunov functions?: An algorithmic approach to systems stability. Sheffield: University of Sheffield, Dept. of Control Engineering, 1989.

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15

Haslach, Henry W. Nonlinear asymptotic integration algorithms for one-dimensional autonomous dissipative first-order ODEs. Washington, DC: National Aeronautics and Space Administration, 1994.

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16

Iliff, Kenneth W. X-29A lateral-directional stability and control derivatives extracted from high-angle-of-attack flight data. [Washington, D.C]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program Center, 1996.

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17

Iliff, Kenneth W. X-29A lateral-directional stability and control derivatives extracted from high-angle-of-attack flight data. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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18

Iliff, Kenneth W. X-29A lateral-directional stability and control derivatives extracted from high-angle-of-attack flight data. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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19

Iliff, Kenneth W. X-29A lateral-directional stability and control derivatives extracted from high-angle-of-attack flight data. Washington, D.C: National Aeronautics and Space Administration, 1996.

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20

Iliff, Kenneth W. X-29A lateral-directional stability and control derivatives extracted from high-angle-of-attack flight data. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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21

Yee, H. C. Dynamical approach study of spurious steady-state numerical solutions of nonlinear differential equations. [Washington, D.C: National Aeronautics and Space Administration, 1990.

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22

Yee, H. C. Dynamical approach study of spurious steady-state numerical solutions of nonlinear differential equations. [Washington, D.C: National Aeronautics and Space Administration, 1990.

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23

W, Porada Theodore, and United States. National Aeronautics and Space Administration., eds. Linearization of digital derived rate algorithm for use in linear stability analysis. [Washington, DC?]: National Aeronautics and Space Administration, 1985.

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24

Kong, Xuan, and Victor Solo. Adaptive Signal Processing Algorithms: Stability and Performance. Prentice Hall, 1994.

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25

Kong, Xuan, and Victor Solo. Adaptive Signal Processing Algorithms: Stability and Performance. Prentice Hall, 1994.

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26

Zhang, Huaguang, Ding Wang, Derong Liu, and Yanhong Luo. Adaptive Dynamic Programming for Control: Algorithms and Stability. Springer, 2015.

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27

Adaptive Dynamic Programming For Control Algorithms And Stability. Springer London Ltd, 2013.

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28

S, Mason Gregory, and United States. National Aeronautics and Space Administration., eds. Multirate sampled-data yaw-damper and modal suppression system design. Washington DC: National Aeronautics and Space Administration, 1991.

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29

S, Mason Gregory, and United States. National Aeronautics and Space Administration., eds. Multirate sampled-data yaw-damper and modal suppression system design. Washington DC: National Aeronautics and Space Administration, 1991.

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30

Mandic, Danilo P., and Jonathon A. Chambers. Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability. Wiley & Sons, Incorporated, John, 2003.

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31

Mandic, Danilo P., and Jonathon A. Chambers. Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability. Wiley & Sons, Incorporated, John, 2002.

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32

Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability. Wiley, 2001.

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33

Toplis, Blake Stephen. Tracking, adaptability and stability modifications for fast recursive least squares algorithms. 1987.

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34

H, Effertz F., and United States. National Aeronautics and Space Administration., eds. The algebraic criteria for the stability of control systems. Washington, D.C: National Aeronautics and Space Administration, 1986.

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35

Ignatyev, Alexander V. DEVELOPMENT OF THE FINITE ELEMENT METHOD IN THE FORM OF THE CLASSICAL MIXED BUILDING MECHANICS METHOD. Thesis for the degree of Doctor of Technical Sciences. Volgograd State Technical University, 2023. http://dx.doi.org/10.12731/dissertation-ignatievav.

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The dissertation states: 1. The main provisions of the theory of the finite element method in the form of a classical mixed method. 2. Methods for obtaining physical and mathematical models of finite elements with mixed unknowns in the main system. 3. Construction of resolving equations based on the obtained mathematical models of finite elements and development of algorithms for their solution. 4. Algorithms for solving problematic problems: accounting for FE displacements as a rigid whole, accounting for rigid inclusions and holes. 5. Features of physical and mathematical models of problems of dynamics and stability of structures and the calculation algorithms that implement them. 6. Physical and mathematical models of reduction methods for lowering the order of large systems of frequency resolving equations. 7. Physical and mathematical models and algorithms for solving geometrically nonlinear problems and problems of calculating structurally nonlinear systems with one-way connections.

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36

United States. National Aeronautics and Space Administration., ed. Global electric field determination in the earth's outer magnetosphere using energetic charged particles. [Washington, DC: National Aeronautics and Space Administration, 1995.

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37

Investigation of cloud properties and atmospheric stability with MODIS: Semi-annual report for Jan - Jun, 1993. [Washington, DC: National Aeronautics and Space Administration, 1993.

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38

United States. National Aeronautics and Space Administration., ed. Investigation of cloud properties and atmospheric stability with MODIS: Semi-annual report for Jan - Jun 1995. [Washington, DC: National Aeronautics and Space Administration, 1995.

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39

Boudreau, Joseph F., and Eric S. Swanson. Ordinary differential equations. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0011.

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This chapter surveys the ordinary differential equations (ODEs) that occur in classical and quantum mechanics, and describes both numerical algorithms and appropriate software design for solving them. Systems of ordinary differential equations, together with a few constants of integration, can in most cases be regarded as a means of defining a function (the “solution”). In this chapter, we develop an object-oriented architecture that applies integrators of the Runge-Kutta family to create these functions. Together with an automatic derivative system for generating partial derivatives from functions of one or more variables, the differential equation solver becomes a powerful tool for solving a variety of few-body problems in classical Hamiltonian systems. This chapter presents a blend of numerical algorithms, physics, and computing techniques. The phenomenon of energy drift is discussed and used to motivate symplectic solvers. Techniques such as adaptive step size and possible problems with stability and multiple scales are also discussed.

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40

Paul, Menzel, and United States. National Aeronautics and Space Administration., eds. Investigation of cloud properties and atmospheric stability with MODIS: Semi-annual report for Jan-Jun 1996 : contract NAS5-31367. [Washington, DC: National Aeronautics and Space Administration, 1996.

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41

Zhu, Yang, and Miroslav Krstic. Delay-Adaptive Linear Control. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691202549.001.0001.

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Actuator and sensor delays are among the most common dynamic phenomena in engineering practice, and when disregarded, they render controlled systems unstable. Over the past sixty years, predictor feedback has been a key tool for compensating such delays, but conventional predictor feedback algorithms assume that the delays and other parameters of a given system are known. When incorrect parameter values are used in the predictor, the resulting controller may be as destabilizing as without the delay compensation. This book develops adaptive predictor feedback algorithms equipped with online estimators of unknown delays and other parameters. Such estimators are designed as nonlinear differential equations, which dynamically adjust the parameters of the predictor. The design and analysis of the adaptive predictors involves a Lyapunov stability study of systems whose dimension is infinite, because of the delays, and nonlinear, because of the parameter estimators. This book solves adaptive delay compensation problems for systems with single and multiple inputs/outputs, unknown and distinct delays in different input channels, unknown delay kernels, unknown plant parameters, unmeasurable finite-dimensional plant states, and unmeasurable infinite-dimensional actuator states. Presenting breakthroughs in adaptive control and control of delay systems, the book offers powerful new tools for the control engineer and the mathematician.

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42

Boudreau, Joseph F., and Eric S. Swanson. Continuum dynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0019.

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The theory and application of a variety of methods to solve partial differential equations are introduced in this chapter. These methods rely on representing continuous quantities with discrete approximations. The resulting finite difference equations are solved using algorithms that stress different traits, such as stability or accuracy. The Crank-Nicolson method is described and extended to multidimensional partial differential equations via the technique of operator splitting. An application to the time-dependent Schrödinger equation, via scattering from a barrier, follows. Methods for solving boundary value problems are explored next. One of these is the ubiquitous fast Fourier transform which permits the accurate solution of problems with simple boundary conditions. Lastly, the finite element method that is central to modern engineering is developed. Methods for generating finite element meshes and estimating errors are also discussed.

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43

Unstructured grid Euler method assessment for longitudinal and lateral/directional stability analysis of the HSR Reference H configuration at transonic speeds. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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44

Charles, Wang Kon-Sheng, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. X-29A lateral-directional stability and control derivatives extracted from high-angle-of-attack flight data. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

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45

Tiwari, Sandip. Information mechanics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198759874.003.0001.

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Information is physical, so its manipulation through devices is subject to its own mechanics: the science and engineering of behavioral description, which is intermingled with classical, quantum and statistical mechanics principles. This chapter is a unification of these principles and physical laws with their implications for nanoscale. Ideas of state machines, Church-Turing thesis and its embodiment in various state machines, probabilities, Bayesian principles and entropy in its various forms (Shannon, Boltzmann, von Neumann, algorithmic) with an eye on the principle of maximum entropy as an information manipulation tool. Notions of conservation and non-conservation are applied to example circuit forms folding in adiabatic, isothermal, reversible and irreversible processes. This brings out implications of fluctuation and transitions, the interplay of errors and stability and the energy cost of determinism. It concludes discussing networks as tools to understand information flow and decision making and with an introduction to entanglement in quantum computing.

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46

Boulton, Jill E., Kevin Coughlin, Debra O'Flaherty, and Alfonso Solimano, eds. ACoRN: Acute Care of at-Risk Newborns. 2nd ed. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780197525227.001.0001.

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The Acute Care of at-Risk Newborns (ACoRN) program trains health care providers to stabilize that most challenging and enigmatic of medical patients: the unwell newborn. Early assessment, intervention, and management of at-risk or unstable infants can be critical for their survival and long-term health. Clinical care standards and educational programs to address these requirements are needed. The ACoRN program provides a unique, prioritized, and systematic approach to newborn stabilization for health care professionals with any degree of experience. ACoRN-trained providers learn to gather information, prioritize, intervene appropriately, and deliver high quality care to at-risk and unwell newborns in any setting. Because research and practice have advanced dramatically in recent years, the need for a new ACoRN text, the program’s centrepiece, became essential—hence the development of this new edition, which reflects current guidelines and evidence-based best practices. ACoRN teaches the concepts and skills required to stabilize unwell newborns through system-based algorithms (Sequences), each with its own chapter: respiratory, cardiovascular, neurology, surgical conditions, fluid and glucose, jaundice, thermoregulation, and infection. The ACoRN mnemonic defines stabilization steps and chapter structure: alerting signs, core steps, organization of care, response, next steps, and specific diagnosis and management. Each chapter includes educational objectives, key concepts, learning points, and at least one case scenario with questions and answers to reinforce content and learnings. This book is written for any health professional who may be required to participate in the stabilization of sick or preterm babies within their scope of practice.

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47

Dynamical approach study of spurious steady-state numerical solutions of nonlinear differential equations. [Washington, D.C: National Aeronautics and Space Administration, 1995.

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48

United States. National Aeronautics and Space Administration., ed. FPCAS2D user's guide, version 1.0. [Washington, DC: National Aeronautics and Space Administration, 1994.

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49

Dahmen, W., and A. Reusken. Numerik für Ingenieure und Naturwissenschaftler (Springer-Lehrbuch). Springer, 2006.

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50

Numerik für Ingenieure und Naturwissenschaftler. Berlin, Germany: Springer, 2006.

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Книги з теми "Algorithm stability"

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