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Mean Dimension for Non-autonomous Iterated Function Systems
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作者 Meng Deyu Zhao Cao 《数学理论与应用》 2024年第3期119-129,共11页
In this paper we introduce the notions of mean dimension and metric mean dimension for non-autonomous iterated function systems(NAIFSs for short)on countably infinite alphabets which can be regarded as generalizations... In this paper we introduce the notions of mean dimension and metric mean dimension for non-autonomous iterated function systems(NAIFSs for short)on countably infinite alphabets which can be regarded as generalizations of the mean dimension and the Lindenstrauss metric mean dimension for non-autonomous iterated function systems.We also show the relationship between the mean topological dimension and the metric mean dimension. 展开更多
关键词 Non-autonomous iterated function system Mean dimension Metric mean dimension
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ITERATED FUNCTION SYSTEM AND GALTON-WATSON TREE
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作者 余旌胡 谢南瑞 《Acta Mathematica Scientia》 SCIE CSCD 2007年第3期456-464,共9页
Given a system {S1,…, SN} of N contractive similarities satisfying some strong separation condition, it has an invariant Set K for the system. In this article, the authors construct some random measure μω supported... Given a system {S1,…, SN} of N contractive similarities satisfying some strong separation condition, it has an invariant Set K for the system. In this article, the authors construct some random measure μω supported on random subset Kω of K, μω having some "non-standard" multifractal structure, which contrasts the well-knoWn multifractal formalism for the invariant measure of system {S1,.., SN} may possess. The main tool is the multifractal structures of a Galton-Watson tree, which are obtained by Liu [9], Shieh-Taylor [14], and MSrters-Shieh [12]. 展开更多
关键词 Multifractal structure iterated function stysem Galton-Watson tree
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Chaos game representation of functional protein sequences,and simulation and multifractal analysis of induced measures 被引量:1
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作者 喻祖国 肖前军 +2 位作者 石龙 余君武 Vo Anh 《Chinese Physics B》 SCIE EI CAS CSCD 2010年第6期556-568,共13页
Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos gam... Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos game representation (CGR) of randomly-linked functional protein sequences, then propose the use of the recurrent iterated function systems (RIFS) in fractal theory to simulate the measure based on their chaos game representations. This method helps to extract some features of functional protein sequences, and furthermore the biological functions of these proteins. Then multifractal analysis of the measures based on the CGRs of randomly-linked functional protein sequences are performed. We find that the CGRs have clear fractal patterns. The numerical results show that the RIFS can simulate the measure based on the CGR very well. The relative standard error and the estimated probability matrix in the RIFS do not depend on the order to link the functional protein sequences. The estimated probability matrices in the RIFS with different biological functions are evidently different. Hence the estimated probability matrices in the RIFS can be used to characterise the difference among linked functional protein sequences with different biological functions. From the values of the Dq curves, one sees that these functional protein sequences are not completely random. The Dq of all linked functional proteins studied are multifractal-like and sufficiently smooth for the Cq (analogous to specific heat) curves to be meaningful. Furthermore, the Dq curves of the measure μ based on their CCRs for different orders to link the functional protein sequences are almost identical if q 〉 0. Finally, the Ca curves of all linked functional proteins resemble a classical phase transition at a critical point. 展开更多
关键词 chaos game representation recurrent iterated function systems functional proteins multifractal analysis
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Upper Bound and Lower Bound Estimate of Monotone Increasing Fractal Function
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作者 MA Guan-zhong YUAN Gui-xia CUI Zhen-wen 《Chinese Quarterly Journal of Mathematics》 CSCD 北大核心 2008年第2期188-194,共7页
Mass distribution principle is one of important tools in studying Hausdorff dimension and Hausdorff measure. In this paper we will give a numerical approximate method of upper bound and lower bound of mass distributio... Mass distribution principle is one of important tools in studying Hausdorff dimension and Hausdorff measure. In this paper we will give a numerical approximate method of upper bound and lower bound of mass distribution function f(x)(it is a monotone increasing fractal function) and its some applications. 展开更多
关键词 FRACTAL mass distribution function iterated function system piecewise anti- Bezier curve
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AN APPLICATION OF HARDY-BOEDEWADT'S THEOREM TO ITERATED FUNCTIONAL EQUATIONS
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作者 张伟年 《Acta Mathematica Scientia》 SCIE CSCD 1995年第3期356-360,共5页
In this paper an iterated functional equation of polynomial type which does not possess the firt order iterative term g(x) is to be discussed. The difficulties resulted from loss of the first order term are overcome b... In this paper an iterated functional equation of polynomial type which does not possess the firt order iterative term g(x) is to be discussed. The difficulties resulted from loss of the first order term are overcome by utilization of Hardy-Boedewadt's theorem. 展开更多
关键词 iterated functional equation iterative root structural operator
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A LAW OF THE ITERATED LOGARITHM FOR NEAREST NEIGHBOR ESTIMATION OF MULTIVARIATE DENSITY FUNCTION
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作者 洪圣岩 陈规景 +1 位作者 孔繁超 高集体 《Acta Mathematica Scientia》 SCIE CSCD 1992年第4期472-478,共7页
Let X be a d-dimensional random vector with unknown density function f(z) = f (z1, ..., z(d)), and let f(n) be teh nearest neighbor estimator of f proposed by Loftsgaarden and Quesenberry (1965). In this paper, we est... Let X be a d-dimensional random vector with unknown density function f(z) = f (z1, ..., z(d)), and let f(n) be teh nearest neighbor estimator of f proposed by Loftsgaarden and Quesenberry (1965). In this paper, we established the law of the iterated logarithm of f(n) for general case of d greater-than-or-equal-to 1, which gives the exact pointwise strong convergence rate of f(n). 展开更多
关键词 A LAW OF THE ITERATED LOGARITHM FOR NEAREST NEIGHBOR ESTIMATION OF MULTIVARIATE DENSITY function exp
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A new fractal algorithm to model discrete sequences
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作者 翟明岳 Heidi Kuzuma James W. Rector 《Chinese Physics B》 SCIE EI CAS CSCD 2010年第9期274-278,共5页
Employing the properties of the affine mappings, a very novel fractal model scheme based on the iterative function system is proposed. We obtain the vertical scaling factors by a set of the middle points in each affin... Employing the properties of the affine mappings, a very novel fractal model scheme based on the iterative function system is proposed. We obtain the vertical scaling factors by a set of the middle points in each affine transform, solving the difficulty in determining the vertical scaling factors, one of the most difficult challenges faced by the fractal interpolation. The proposed method is carried out by interpolating the known attractor and the real discrete sequences from seismic data. The results show that a great accuracy in reconstruction of the known attractor and seismic profile is found, leading to a significant improvement over other fractal interpolation schemes. 展开更多
关键词 fractal interpolation the vertical scaling factors iterative function system seismic data
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