Comparative reduction of theories — or over-simplification?

1996 ◽  
Vol 19 (2) ◽  
pp. 301-302 ◽  
Author(s):  
Edgar Koerner
Keyword(s):  
Phase Transitions ◽  
State Space ◽  
Functional Diversity ◽  
Chaotic Systems ◽  
General Scheme ◽  
Systems Dynamics ◽  
Rapid Phase ◽  
Cortical Dynamics ◽  
Control Forces

AbstractTo model the organization of levels' of cortical dynamics, at least some general scheme for hierarchy, functional diversity, and proper intrinsic control must be provided. Rhythmic control forces the system to iterate its state by short trajectories, which makes it much more stable and predictable without discarding the desirable ability of chaotic systems to make rapid phase transitions. Rhythmic control provides a fundamentally different systems dynamics, one not provided by models that allow the emergence of continuous trajectories in the systems state space.

scholarly journals A combined fluid-dynamic and thermodynamic model to predict the onset of rapid phase transitions in LNG spills

2020 ◽  
pp. 104354
Author(s):  
Karl Yngve Lervåg ◽  
Hans Langva Skarsvåg ◽  
Eskil Aursand ◽  
Jabir Ali Ouassou ◽  
Morten Hammer ◽  
...  
Keyword(s):  
Phase Transitions ◽  
Thermodynamic Model ◽  
Fluid Dynamic ◽  
Rapid Phase

Mixed Strategy Global Sub-Optimal Feedback Control for Chaotic Systems

1997 ◽  
Vol 07 (03) ◽  
pp. 607-623 ◽  
Author(s):  
H. W. J. Lee ◽  
M. Paskota ◽  
K. L. Teo
Keyword(s):  
Feedback Control ◽  
State Space ◽  
Chaotic Systems ◽  
Mixed Strategy ◽  
The State ◽  
Optimal Feedback Control ◽  
Target Region ◽  
Optimal Feedback ◽  
Control Scheme

How to perform targeting of chaotic systems in a global sense is an important question. In this paper, we address this problem by introducing a mixed strategy global sub-optimal feedback control scheme. The idea is to partition the state space into 2 parts, namely, the target region and its complement. The proposed controller will take different forms depending on which partition of the state space the system is in. Simulations are also provided to illustrate the proposed scheme.

scholarly journals CUMULATIVE MEASURE OF CORRELATION FOR MULTIPARTITE QUANTUM STATES

2014 ◽  
Vol 28 (07) ◽  
pp. 1450050 ◽  
Author(s):  
ANDRÉ L. FONSECA DE OLIVEIRA ◽  
EFRAIN BUKSMAN ◽  
JESÚS GARCÍA LÓPEZ DE LACALLE
Keyword(s):  
Phase Transitions ◽  
State Space ◽  
Present Article ◽  
Critical Points ◽  
Quantum Phase Transitions ◽  
The State ◽  
Quantum States ◽  
Quantum Phase ◽  
Mixed States ◽  
Different Dimensions

The present article proposes a measure of correlation for multiqubit mixed states. The measure is defined recursively, accumulating the correlation of the subspaces, making it simple to calculate without the use of regression. Unlike usual measures, the proposed measure is continuous additive and reflects the dimensionality of the state space, allowing to compare states with different dimensions. Examples show that the measure can signal critical points (CPs) in the analysis of Quantum Phase Transitions (QPTs) in Heisenberg models.

Phase transitions associated with dynamical properties of chaotic systems

1987 ◽  
Vol 36 (7) ◽  
pp. 3525-3528 ◽  
Author(s):  
P. Szépfalusy ◽  
T. Tél ◽  
A. Csordás ◽  
Z. Kovács
Keyword(s):  
Phase Transitions ◽  
Chaotic Systems ◽  
Dynamical Properties

scholarly journals Rapid phase transitions in local SUSY guts

1983 ◽  
Vol 129 (3-4) ◽  
pp. 223-228 ◽  
Author(s):  
C. Kounnas ◽  
D.V. Nanopoulos ◽  
M. Quiros
Keyword(s):  
Phase Transitions ◽  
Rapid Phase

Rapid‐phase transitions of GeTe‐Sb2Te3pseudobinary amorphous thin films for an optical disk memory

1991 ◽  
Vol 69 (5) ◽  
pp. 2849-2856 ◽  
Author(s):  
Noboru Yamada ◽  
Eiji Ohno ◽  
Kenichi Nishiuchi ◽  
Nobuo Akahira ◽  
Masatoshi Takao
Keyword(s):  
Thin Films ◽  
Phase Transitions ◽  
Optical Disk ◽  
Rapid Phase ◽  
Amorphous Thin Films ◽  
Disk Memory

NEURAL NETWORK-BASED DIGITAL REDESIGN APPROACH FOR CONTROL OF UNKNOWN CONTINUOUS-TIME CHAOTIC SYSTEMS

2005 ◽  
Vol 15 (08) ◽  
pp. 2433-2455
Author(s):  
JOSE I. CANELON ◽  
LEANG S. SHIEH ◽  
SHU M. GUO ◽  
HEIDAR A. MALKI
Keyword(s):  
Neural Network ◽  
State Space ◽  
Continuous Time ◽  
Digital Control ◽  
Chaotic Systems ◽  
Linear Time ◽  
The State ◽  
Control Law ◽  
Analog Control ◽  
Digital Redesign

This paper presents a neural network-based digital redesign approach for digital control of continuous-time chaotic systems with unknown structures and parameters. Important features of the method are that: (i) it generalizes the existing optimal linearization approach for the class of state-space models which are nonlinear in the state but linear in the input, to models which are nonlinear in both the state and the input; (ii) it develops a neural network-based universal optimal linear state-space model for unknown chaotic systems; (iii) it develops an anti-digital redesign approach for indirectly estimating an analog control law from a fast-rate digital control law without utilizing the analog models. The estimated analog control law is then converted to a slow-rate digital control law via the prediction-based digital redesign method; (iv) it develops a linear time-varying piecewise-constant low-gain tracker which can be implemented using microprocessors. Illustrative examples are presented to demonstrate the effectiveness of the proposed methodology.

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