?-Entropy, ?-capacity, and approximative dimension for containing spaces of the classesH p ,p<1

1974 ◽  
Vol 78 (3) ◽  
pp. 267-277
Author(s):  
Niro Yanagihara ◽  
Shin Kawase
Keyword(s):  
Entropy Capacity

Entropy capacity determines protein folding

2006 ◽  
Vol 63 (1) ◽  
pp. 144-154 ◽  
Author(s):  
Oxana V. Galzitskaya ◽  
Sergiy O. Garbuzynskiy
Keyword(s):  
Protein Folding ◽  
Entropy Capacity

scholarly journals Entropy sets, weakly mixing sets and entropy capacity

2008 ◽  
Vol 20 (2) ◽  
pp. 275-311 ◽  
Author(s):  
François Blanchard ◽  
◽  
Wen Huang ◽  
Keyword(s):  
Weakly Mixing ◽  
Entropy Capacity

scholarly journals Variation of the entropy analysis method in information flows of IBS in the concept of safe navigation development

2021 ◽  
Vol 2061 (1) ◽  
pp. 012107
Author(s):  
AA Vasiutina ◽  
VV Popov ◽  
AI Kondratyev
Keyword(s):  
Intelligent Control ◽  
Integrated System ◽  
Analysis Method ◽  
Artificial Neuron ◽  
Object Control ◽  
Safe Navigation ◽  
Management Personnel ◽  
Directional Control ◽  
Entropy Capacity ◽  
Control Machine

Abstract The creation of a configuration by a bridge integrated system in the form of the control machine variation - artificial intelligence, becomes relevant in the concept of E-navigation development with the vector of the vessel’s directional control on the course, both in a small crew and unmanned way. It is possible to consider a large number of mathematical ideas about the basis for creating an intelligent control machine: an artificial neuron and fuzzy sets, Petri nets and Markov chains, Kolmogorov’s differential equations, which are difficult to configure and cumbersome to compute. Multiagent systems seem to be feasible. Integrated bridge systems with embedded supplementary reality assist management personnel in solving navigation issues. Saturation of the navigation control information complex of the bridge system with an increasing number of hardware and instrument units leads to a decrease in information entropy but does not bring to the full automatic control. In ergatic systems, object control is still reduced to declining the uncertainty to a minimum value by means of the operator’s control actions. The methodology for analyzing the entropy capacity of the system and elements of the augmented virtual assessment of the situation in the configuration of multifunctional machine units can be applied in the efficiency criteria development for vessel’s control systems with small crew or unmanned navigation in the concept of E-navigation.

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