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Books on the topic 'Complex Dynamic Systems Theory (CDST)'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Fogal, Gary G., and Marjolijn H. Verspoor, eds. Complex Dynamic Systems Theory and L2 Writing Development. Amsterdam: John Benjamins Publishing Company, 2020. http://dx.doi.org/10.1075/lllt.54.

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2

Herbert, Praehofer, and Kim Tag Gon, eds. Theory of modeling and simulation: Integrating discrete event and continuous complex dynamic systems. 2nd ed. San Diego: Academic Press, 2000.

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3

Southeast Geometry Seminar (15th 2009 University of Alabama at Birmingham). Geometric analysis, mathematical relativity, and nonlinear partial differential equations: Southeast Geometry Seminars Emory University, Georgia Institute of Technology, University of Alabama, Birmingham, and the University of Tennessee, 2009-2011. Edited by Ghomi Mohammad 1969-. Providence, Rhode Island: American Mathematical Society, 2013.

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4

Fogal, Gary G., and Marjolijn H. Verspoor. Complex Dynamic Systems Theory and L2 Writing Development. Benjamins Publishing Company, John, 2020.

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5

Fogal, Gary G., and Marjolijn H. Verspoor. Complex Dynamic Systems Theory and L2 Writing Development. Benjamins Publishing Company, John, 2020.

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6

Fogal, Gary G., and Marjolijn H. Verspoor. Complex Dynamic Systems Theory and L2 Writing Development. Benjamins Publishing Company, John, 2020.

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7

Boukas, El-Kébir, and Roland P. Malhamé. Analysis, Control and Optimization of Complex Dynamic Systems. Springer, 2014.

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8

(Editor), El Kébir Boukas, and Roland P. Malhamé (Editor), eds. Analysis, Control and Optimization of Complex Dynamic Systems (Gerad 25th Anniversary). Springer, 2005.

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9

Analysis, Control and Optimization of Complex Dynamic Systems (Gerad 25th Anniversary). Springer, 2005.

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10

Aihara, Kazuyuki, Tetsushi Ueta, and Jun-ichi Imura. Analysis and Control of Complex Dynamical Systems: Robust Bifurcation, Dynamic Attractors, and Network Complexity. Springer, 2016.

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11

Aihara, Kazuyuki, Tetsushi Ueta, and Jun-ichi Imura. Analysis and Control of Complex Dynamical Systems: Robust Bifurcation, Dynamic Attractors, and Network Complexity. Springer London, Limited, 2015.

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12

Aihara, Kazuyuki, Tetsushi Ueta, and Jun-ichi Imura. Analysis and Control of Complex Dynamical Systems: Robust Bifurcation, Dynamic Attractors, and Network Complexity. Springer, 2015.

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13

Leondes, C. T. Analysis and Synthesis Techniques in Complex Control and Dynamic Systems: Advances in Theory and Applications. Elsevier Science & Technology Books, 1994.

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14

Modeling, Control and Optimization of Complex Systems: In Honor of Professor Yu-Chi Ho (The International Series on Discrete Event Dynamic Systems). Springer, 2002.

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15

Advances in Artificial Economics: The Economy as a Complex Dynamic System (Lecture Notes in Economics and Mathematical Systems). Springer, 2006.

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16

Succi, Sauro. Kinetic Theory of Dense Fluids. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199592357.003.0007.

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This chapter presents the basic elements of the kinetic theory of non-ideal fluids, to which both kinetic and potential energy contribute on comparable footing. Non-ideal fluids lie at the heart of many complex fluid-dynamic applications, such as those involving multiphase and multicomponent flows. This chapter features a degree of abstraction which may not come by handy to the reader with limited interest to the formal theory of classical many-body systems. The interested readers can safely skip the math and retain the basic bottomline. They may just skip this chapter altogether, but in this author’s opinion, this is likely to come with a toll on the full appreciation of Lattice Boltzmann theory for non-ideal fluids, in fact one of the most successful offsprings of Lattice Boltzmann theory.

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17

Lopotenco, Viorica. DEVELOPMENT OF THE NEW INTERNATIONAL FINANCIAL ARCHITECTURE AT THE NATIONAL FINANCIAL SYSTEMS LEVEL. RS Global S. z O.O., 2020. http://dx.doi.org/10.31435/rsglobal/027.

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The fundamental purpose of this paper is to analyze the transformations in the international financial architecture and their impact on the national financial system. The analysis of the international financial architecture's functioning mechanism suggests its similarity with the software system structure. It is static in the way the system functionality is decomposed and divided into implementation teams. The efficiency of international financial architecture's functioning depends mainly on how balanced and interconnected its elements are. Thus, according to systems theory, only by overcoming the deformation of the international financial architecture at all its levels, it is possible to increase the financial system's overall performance. In this regard, maintaining a dynamic balance in the development of the international financial architecture as an integral unit of its structural elements and functions is becoming of urgent importance. This aspect of the research allows the creation of an instrumental and methodological basis for forecasting the directions for further developing the international financial architecture in the context of the globalization of the world economy at the national financial systems level. This study concludes that the complex solution of the international financial architecture challenges involves creating the foundations for implementing progressive structural changes in the economy and contributing to sustainable economic development.

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18

Koch, Christof. Biophysics of Computation. Oxford University Press, 1998. http://dx.doi.org/10.1093/oso/9780195104912.001.0001.

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Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes. Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation. Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

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