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Two-dimensional cellular automaton evolution rule classification method

A cellular automata, two-dimensional cellular technology, applied in computer parts, instruments, characters, and pattern recognition, etc., can solve the problem of reducing the number of evolution rules, unable to complete non-additive evolution rule classification processing, and inconsistency of evolution rules. It belongs to the stable type and other problems, and achieves the effect of improving accuracy, low universality, and high classification accuracy.

Inactive Publication Date: 2017-12-19
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

If in the evolution space of cellular automata, the proportion of living cells in one part of the space has decreased a lot, while the proportion of living cells in another part of the space has increased a lot, if the proportion of decline is similar to the proportion of rise, resulting in The proportion of living cells in the entire evolution space remains stable, but in fact the evolution rule of this kind of cellular automata is not stable
[0007] The existing classification methods classify the evolution rules of additive two-dimensional cellular automata, but cannot complete the classification processing of non-additive evolution rules, reducing a large number of evolution rules

Method used

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  • Two-dimensional cellular automaton evolution rule classification method

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Embodiment

[0050] In this embodiment, the size of the two-dimensional cell space is 200×200, and the number of evolution time steps (system operation steps) of the evolution rule is 400 steps. "1" is used to represent the state of the raw cell, and "0" is represented as The dead cell state neighbor model is VonNeumann, and the domain radius is set to 5. The settings of each threshold are: α=0.90, β=0.18, χ=0.5, δ=0.8. The two-dimensional cellular automaton numbers are classified from 1 to 1,000,000 evolution rules, and the classification method of the present invention is used to complete the classification, and the percentage of each type accounting for the total number of 1,000,000 is counted, as shown in Table 1 below:

[0051] Table 1 Proportion of evolution rules of four types of two-dimensional cellular automata

[0052]

[0053]

[0054] In Table 1, among the evolution rules of two-dimensional cellular automata, the stable type and the periodic type account for more than ha...

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Abstract

The invention discloses a two-dimensional cellular automaton evolution rule classification method and belongs to the technical field of a cellular automaton. According to the method, under the random initial conditions, statistics of change conditions of cellular states of each position in the certain-scale evolution space is carried out, and classification is carried out; if within plenty of continuous time steps, the evolution space at each time and the stable evolution space have non-big difference, and the evolution space is a stationary type; if within plenty of continuous time steps, one period exists, the evolution space at each time in the period and the evolution space at the time of the next period have non-big difference, the evolution space is a period type; if within plenty of continuous time steps, the evolution space at each time is complex, the evolution space at one time has a relatively large quantity of cellulars in an update state compared with the evolution space at the previous time, update is irregular, the evolution space is a complex type; otherwise, the evolution space is a confused type. The method is advantaged in that the method can be applied to image encryption and image compression, application evolution rules are wide, and accurate classification can be realized.

Description

technical field [0001] The invention belongs to the technical field of cellular automaton (Cellular Automaton), and specifically relates to a classification process based on evolution rules of two-dimensional cellular automaton. Background technique [0002] A cellular automaton is a dynamical system that is discrete in time and space. Each cell (Cell) scattered in the evolution rule grid (LatticeGrid) takes a finite discrete state, follows the same action evolution rule, and performs synchronous update according to the determined local evolution rule. A large number of cells constitute the evolution of the fine state system through simple interactions. [0003] People classify the evolution rules of cellular automata from different angles, such as dynamics, linguistics, topology, and dimensions. Wolfram's qualitative classification of evolution rules for one-dimensional cellular automata in terms of dynamical behavior is by far the most influential. Researchers have done...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/2431
Inventor 邢建川王帅飞韩保祯张易丰丁志新翟能延胡尊天王翔康亮张栋王书琪侯鑫宇沈浩陈朝阳苗佳雨蔡佳宏王鋆鼎李双陈佳豪刘继林杨双吉邵慧梁昌乐颜文杰尹佳
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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