On Dynamic Systems with Random Perturbations

1974 ◽  
Vol 18 (4) ◽  
pp. 678-693
Author(s):  
V. M. Tutubalin
Keyword(s):  
Dynamic Systems ◽  
Random Perturbations

scholarly journals A Bayes Estimator of Parameters of Nonlinear Dynamic Systems

2009 ◽  
Vol 2009 ◽  
pp. 1-21 ◽  
Author(s):  
I. A. Boguslavsky
Keyword(s):  
Dynamic Systems ◽  
Matrix Inversion ◽  
Random Perturbations ◽  
Evolutionary System ◽  
The Monte Carlo Method ◽  
Approximation Errors ◽  
Discrete Time Observations ◽  
Polynomial Series ◽  
Observational Errors ◽  
Vector Polynomial

A new multipolynomial approximations algorithm (the MPA algorithm) is proposed for estimating the state vectorθof virtually any dynamical (evolutionary) system. The input of the algorithm consists of discrete-time observationsY. An adjustment of the algorithm is required to the generation of arrays of random sequences of state vectors and observations scalars corresponding to a given sequence of time instants. The distributions of the random factors (vectors of the initial states and random perturbations of the system, scalars of random observational errors) can be arbitrary but have to be prescribed beforehand. The output of the algorithm is a vector polynomial series with respect to products of nonnegative integer powers of the results of real observations or some functions of these results. The sum of the powers does not exceed some given integerd. The series is a vector polynomial approximation of the vectorE(θ∣Y), which is the conditional expectation of the vector under evaluation (or given functions of the components of that vector). The vector coefficients of the polynomial series are constructed in such a way that the approximation errors uniformly tend to zero as the integerdincreases. These coefficients are found by the Monte-Carlo method and a process of recurrent calculations that do not require matrix inversion.

Phase behavior of cationic and anionic surfactants at low concentrations

1992 ◽  
Vol 50 (1) ◽  
pp. 694-695
Author(s):  
E. Naranjo
Keyword(s):  
Phase Behavior ◽  
Structural Characterization ◽  
Dynamic Systems ◽  
Anionic Surfactants ◽  
Intermolecular Forces ◽  
Stable Form ◽  
Surfactant Mixtures ◽  
Low Concentrations ◽  
Cationic And Anionic Surfactants ◽  
General Method

Equilibrium vesicles, those which are the stable form of aggregation and form spontaneously on mixing surfactant with water, have never been demonstrated in single component bilayers and only rarely in lipid or surfactant mixtures. Designing a simple and general method for producing spontaneous and stable vesicles depends on a better understanding of the thermodynamics of aggregation, the interplay of intermolecular forces in surfactants, and an efficient way of doing structural characterization in dynamic systems.

Improving Feeding Outcomes in the NICU: Moving From Volume-Driven to Infant-Driven Feeding

2010 ◽  
Vol 19 (3) ◽  
pp. 68-74 ◽  
Author(s):  
Catherine S. Shaker
Keyword(s):  
Intensive Care Unit ◽  
Dynamic Systems ◽  
Neonatal Intensive Care ◽  
Well Being ◽  
Dynamic Systems Theory ◽  
Feeding Problems ◽  
Care Giving ◽  
Extremely Preterm ◽  
Extremely Preterm Infants

Current research on feeding outcomes after discharge from the neonatal intensive care unit (NICU) suggests a need to critically look at the early underpinnings of persistent feeding problems in extremely preterm infants. Concepts of dynamic systems theory and sensitive care-giving are used to describe the specialized needs of this fragile population related to the emergence of safe and successful feeding and swallowing. Focusing on the infant as a co-regulatory partner and embracing a framework of an infant-driven, versus volume-driven, feeding approach are highlighted as best supporting the preterm infant's developmental strivings and long-term well-being.

A Dynamic Systems Approach to Personality

2001 ◽  
Vol 6 (3) ◽  
pp. 172-176 ◽  
Author(s):  
Lawrence A. Pervin
Keyword(s):  
Dynamic Systems ◽  
Systems Approach ◽  
Biological Processes ◽  
Recent Advances ◽  
Dynamic View ◽  
The Future ◽  
History Of

David Magnusson has been the most articulate spokesperson for a holistic, systems approach to personality. This paper considers three concepts relevant to a dynamic systems approach to personality: dynamics, systems, and levels. Some of the history of a dynamic view is traced, leading to an emphasis on the need for stressing the interplay among goals. Concepts such as multidetermination, equipotentiality, and equifinality are shown to be important aspects of a systems approach. Finally, attention is drawn to the question of levels of description, analysis, and explanation in a theory of personality. The importance of the issue is emphasized in relation to recent advances in our understanding of biological processes. Integrating such advances into a theory of personality while avoiding the danger of reductionism is a challenge for the future.

Dynamic Systems for Everyone

1996 ◽  
Vol 41 (10) ◽  
pp. 1002-1003
Author(s):  
Esther Thelen
Keyword(s):  
Dynamic Systems
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