ON THE ALGORITHMIC COMPLEXITY OF STATIC STRUCTURES
ON THE ALGORITHMIC COMPLEXITY OF STATIC STRUCTURES
摘要
This paper provides a first indication that this is true for a system comprised of a static structure described by hyperbolic partial differential equations and is subjected to an external random input force. The system deforms the randomness of an input force sequence in proportion to its algorithmic complexity. The authors demonstrate this by numerical analysis of a one-dimensional vibrating elastic solid (the system) on which we apply a maximally-random force sequence (input). The level of complexity of the system is controlled via external parameters. The output response is the field of displacements observed at several positions on the body. The algorithmic complexity and stochasticity of the resulting output displacement sequence is measured and compared against the complexity of the system. The results show that the higher the system complexity, the more random-deficient the output sequence.
参考文献20
-
1G. J. Chaitin, A theory of program size formally identical to information theory, Journal of the ACM, 1975, 22(3): 329-340.
-
2A. V. Deshmukh, J. Talavage, and M. Barash, Complexity in manufacturing systems, part 1: Analysis of static complexity, IIE Transactions, 1998, 30(7): 645-655.
-
3V. V. Vyugin, Algorithmic complexity and stochastic properties of finite binary sequences, The Computer Journal, 1999, 42: 294-317.
-
4J. Ratsaby, An algorithmic complexity interpretation of Lin's third law of information theory, Entropy, 2008, 10(1): 6-14.
-
5J. Ratsaby, On the randomness in learning, Proc. of 7 th IEEE International Conference on Computational Cybernetics, ( ICCC'09), 2009: 141-145.
-
6J. Ratsaby, On the sysratio and its critical point, Mathematical and Computer Modelling, 2010.
-
7J. Ratsaby, Some consequences of the complexity of intelligent prediction, Broad Research in Artificial Intelligence and Neuroscience, 2010, 1(3): 113-118.
-
8J. Ratsaby, On the relation between a system's complexity and its interaction with random environments, Proceedings of International symposium on stochastic models in reliability engineering, life sciences and operations management (SMRLO'10), 2010: 893-901.
-
9J. Ratsaby, An empirical study of the complexity and randomness of prediction error sequences, Communications in Nonlinear Science and Numerical Simulation, in Press, 2010.
-
10J. Ratsaby and I. Chaskalovic, Random patterns and complexity in static structures, Proc. of International Conference on Artificial Intelligence and Pattern Recognition ( AIPR '09), Mathematics and Computer Science, 2009: 255-261.
-
1Chihung Chi,Ye Zhou,Xiaojun Ye.Performance Prediction for Performance-Sensitive Queries Based on Algorithmic Complexity[J].Tsinghua Science and Technology,2013,18(6):618-628.
-
2刘会超,吴志健,李焕哲,王智超.基于差分演化算法的双曲型方程参数识别[J].武汉大学学报(理学版),2015,61(2):117-123. 被引量:1
-
3徐启程,孙常春,赵恩良.随机系统的切换控制[J].计算技术与自动化,2009,28(1):22-26.
-
4胡光华.计算神经生物学与聚类入门[J].国外科技新书评介,2010(1):15-16.
-
5韩会敏,王忠仁,邓文红.基于手持设备人机交互应用的架构设计与开发框架[J].中国民航飞行学院学报,2005,16(4):46-49. 被引量:2
-
6Solid.永恒国度 悠久之仁 100亿次不同的旅程![J].游戏机实用技术,2008(4):105-105.
-
7王志军.让Excel数据随机输入值实现正态分布[J].电脑知识与技术(经验技巧),2015,0(6):44-44.
-
8傅勤.分布参数系统于W^(1,2)空间中的迭代学习控制[J].数学物理学报(A辑),2016,36(2):267-286. 被引量:2
-
9相迎军,李兴城,李传军.基于AT89C4051单片机的专用信号发生器设计与应用[J].微计算机信息,2004,20(11):107-108. 被引量:1
-
10图像采集卡不可或缺[J].现代制造,2013(24):44-45.