Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year.
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RESEARCH INVENTY: International Journal of Engineering and ScienceISSN: 2278-4721, Vol. 1, Issue 7(November 2012), PP 42-45www.researchinventy.com Some Inequalities on the Hausdorff Dimension In The Ricker Population Model Dr. Nabajyoti Das , Assistant Professor, Department of Mathematics, Jawaharlal Nehru College, Boko,Kamrup 781 123, Assam, IndiaAbstract : In this paper, we consider the Ricker population model , where r is the controlparameter and k is the carrying capacity, and obtain some interesting inequalities on the Hausdorff dimension. Ouridea can be extended to Higher dimensional models for further investigation in our research field.Key Words: Hausdorff dimension / Ricker’s model / Fractals 2010subject classification : 37 G 15, 37 G 35 ,37 C45 I. Introduction One natural question with a dynamical system is: how chaotic is a system’s chaotic behavior ? To give aquantitative answer to that question , the dimension theory plays a crucial role . Why is dimensionality important ?One possible answer is that the dimensionality of the state space is closely related to dynamics. The dimensionalityis important in determin ing the range of possible dynamical behavior. Similarly, the dimensionality of anattractor tells about the actual long- term dynamics. A mong various dimensions, Hausdorff dimension plays a veryimportant role as a fractal d imension and measure of chaos , [1,2,5,6,9].We first define Hausdorff Measure as follo ws:If U is any nonempty subset of n- dimensional Euclidean space, Rn , the diameter of U is defined asU sup x y : x, y U , i.e. the greatest distance apart of any pair of points in U . If {Ui } is a countable [or fin ite] collection of sets of distance at most that covers F , i.e. F i 1U i with 0 U i for each i, we say that {Ui } is a cover of F Rn and < 1 , Suppose that F is a subset of Rn and s is a nonnegative number. For any > 0 , we define s H s ( F ) inf{ U i : {U i } is a - cover of F } (1.1 ) i 1As decreases, the class of permissible covers of F in ( 1.1) is reduced. Therefore, the infimu m H s (F )increases, and so approaches a limit as → 0 . We write lim H F . We call s s sH (F) = H (F) the s- dimensional Hausdorff Measure of F . It is clear that for any 0given set F , H s (F ) is non-increasing with s , so Hs (F) is also non- increasing. In fact, if t > s and {Ui } is a -cover of F we haveU Ui U i t s U i t t s s s i i i iSo, taking infima , H (F ) y t s H s . Letting → 0 , we see that H s (F) < ∞ . Thus, Hs (F) = 0 fo r t > s .Hence a graph of Hs (F) against s shows that there is a critical value of s at which Hs (F) ju mps from ∞ to 0 .This crit ical value is called the Hausdorff dimension of F and written as dimH (F). Formally,DimH (F) = inf { s ≥ 0 : Hs (F) =0 } = sup { s : Hs (F) = ∞ } so thatHs (F) = ∞ if 0 ≤ s < dimH (F) and 0 if s > d imH (F) . 42
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Some Inequalities On The Hausdorff Dimension In…If s = dimH (F), then Hs (F) = may be zero or in fin ite , or may satisfy 0 < Hs (F) < ∞ . Fig 1 : Graph of Hs (F) against s for a set F . The Haus dorff di mension is the val ue of s at which the “jump” from ∞ to 0 occurs . Some alternative equivalent definitions for Hausdorff dimension and the method of calculation areavailable in [6] . It is important to note that most dimension calculations involve an upper estimate and a lowerestimate, which are hopefully equal. Each of these estimates usually involves a geometric observa tion follo wed by acalculation , [3,6,7,10] II. The Main Results:CALCULATION OF HAUS DORFF DIMENS ION: [ 5,6,8] Let us consider the model . We take the parameter value and the constant value in sucha way that the function becomes contracting. So as shown in the graph we can take x1 and x2 such that the functionbecomes Fig 2 . Being a unimodel function, if we consider the inverse of f it willgive us two values in that particular range. Let us consider the two inverse functions as s 1 (x) and s 2 (x) ,where and . [fro m the figure 2 we can see thedomain and range.] 43
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Some Inequalities On The Hausdorff Dimension In…To get the Hausdroff dimension we use the following two propositions heavily: A.Proposition 9.6 in the book fractal geometry by Kennith Falconer,[6] states:Let F be the attractor of an IFS consists of contractions {s 1 .s2 ,….,s m} on a closed subset D of Rn such that (x,y ) with o<ci <1 for each i. Then dimH F s , where B.Proposition 9.7 in the book fractal geomet ry by Kennith Falconer,[] states: Let F be the attractor of an IFS consists of contractions {s 1 .s2 ,….,s m} on a closed subset D of Rn such that (x,y ) with o< b i <1 for each i.Then dimH F s , where So we shall try to use these two theorems to calculate the Hausdroff dimension.By their properties we have f(s i (x)) = x for i =1,2. So we have (1.2) , [as f(x)=x er(1-x/k)] for i =1,2. Solving this equation we may get thefunctions s i (x). However solving this type of nonlinear equation analytically is not so easy. We differentiate equation (1.2) w.r.t x and we get ,fo r i=1,2If we again d ifferentiate we have … ( 1.3)The maximu m or min imu m value occurs at s(x)= 2k/r, which is the end point of the definition of our function (if weconsider 2k/r as the end point). Clearly >0 for s 1 (x) (as s 1 (x) < k/r , we can see this fro m the above figure). Sos 1/ (x) is an increasing function. Hence the bounds are given by as follows where s means s 1 .Again we have x1 >0 .Fro m this we get … ( 1.4) Again we consider the equation (1.4) for s = s 2.As k/r<s 2 (x)<2k/rThat is , 1 < r s 2 (x)/k < 2That is, -1>- r s 2 (x)/k >- 2 or, 0>1- r s 2 (x)/k >- 1 Hence for s 2 (x) .So s 2 / (x) is a decreasing function. Again we see s 2 (x) is also decreasing function. Hencethe bounds are given by (1.5)Where s means s 2 .If 2k/r lies in the range of s 2 then the bounds becomesMax and min of { ,-e(2- r)} (1.6)The Hausdorff dimension of our model lies in between the maximu m and the min imu m values obtained from (1.6) . III. Conclusion We select the upper and lower bound for where s means s1 and s2 from propositions (A) and (B), sayc1 and c2 then the upper and lower bounds of the Hausdroff dimension will be {a1,a2} where 2.c1 a1 =1 and 2.c2a2=1 . If we are not satisfied with the bounds then we may go for the composit e mappings like s 1s1 ,s1s 2 ,s 2s2,s 2s1.As s1is an increasing function so s 1s 1, s 1s2. Moreover, as s2 is a decreasing function so is s 2s 2,s2 s1. Again s 1s2:[s 2 (x2 ),s 2 (x1 )] [s 1s2 x2 ,s 1s 2 x1 ].For all these we need [s1 x1 ,s 1 x2 ] [x1 ,x2 ] unfortunately these does not happen all thetime. But if we take x1 and x2 as the fixed points then there will be no problem, again in our case 0 is one obviousfixed point if we consider 0 then our function will no longer be contracting so we have to see other fixed pointsother than 0 . So if we go with the fixed points then proceeding with the above procedure exactly in the same waywe may further contract the bounds, and hence get a better Hausdroff dimension. 44
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Some Inequalities On The Hausdorff Dimension In… Reference[1] K. Alligood, T . Sauer, and J. Yorke, “ Chaos”: An Introduction to Dynamical Systems, New York: Spinger–Verlag, 1997.[2] J. Andres and J. Libor ,“Period three plays a negative role in a multivalued version of Sharkovskii’s theorem” , Non linear Anal. 51,11 1 0- 0 ,2 0 4 02[3] T. Bedford, “Dimension and Dynamics for Fractal Recurent ets”, J. London Mathematical Society, vol 33, pp89 - 100, 1986[4] A. Brännström and D.J. Sumpter , “ The role of competition and clustering in population dynamics.” Proc Biol Sci., Oct 7 272 (1576) : 2065–72 (1) , 2005 .[5] Dennis Brian, R.A. Desharnais, J.M. Cushing and R.F. Costantino , Nonlinear Demographic Dynamics: Mathematical Models, Statiscal Methods and Biological Experiments,Ecological Monographs,” 65 (3), 261 - 281(Ecological Society of America), 1995[6] Kenneth Falconer, “Fractal Geometry, Mathematical Foundations and Applications” , John Wiley & Sons , 2000[7] J. Gewexe and S. Porter-Hudan, “The Estimation and Application of Long Memory Time Series Models”, J. Time Series Anal, vol 4, Pp 221- 228, 1983[8] J.W. Havstad and C.L. Ehlers, “ Attractor Dimension of Nonstationary Dynamical Systems from Small Data Sets”, Physics Rev A 39, 845- 53, 2005[9] A. J. Homburg , “Periodic attractors, strange attractors and hyperbolic dynamics near homoclinic orbits to saddle focus equilbria. Nonlinearity 15 (2002) 1029-1050, 2002[10] H.M. Wu , The Hausdroff dimension of chaotic sets generated by a continuous map from [a , b] intoitself.” J. South China Univ. Natur. Sci. Ed. 45-51 , 2002 45
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