• 沒有找到結果。

Checking all cases in section4.2 can let A n be prim- prim-itive for all n 2

4 Examples for safe symbol existing Case

4.3 Checking all cases in section4.2 can let A n be prim- prim-itive for all n 2

We separate these cases into four subsections.

4.3.1 s2 = b11 or b44 and one column and one row of A are all zero We consider the case1 and case2 in section4.2.

Example 14 Consider A2 = 0

By (2:1) ; it is easily checked that

(1) A2 and A3 =

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

Example 15 Consider A2 =

By (2:1) ; it is easily checked that

(1) A2 and A3 =

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

4.3.2 A is full matrix

We consider the case3 in section4.2.

Example 16 Consider A2 = 0

By (2:1) ; it is easily checked that

(1) A2 and A3 =

(2) there exists

0 = 1; 1 = 1; 2 = 1 and

s2 = b11; s3 = b11b11= s2b11

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

4.3.3 s2 = b11 or b44 and two column and row of A are all zero We consider the case4~case9 in section4.2.

Example 17 Consider

By (2:1) ; it is easily checked that

(1) A2 and A3 =

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

Example 18 Consider

By (2:1) ; it is easily checked that

(1) A2 and A3 =

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

By (2:1) ; it is easily checked that

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

4.3.4 s2 = b14; s3 = b14b44 and two column and row of A are all zero We consider the case10 and case11 in section4.2.

Example 20 Consider

By (2:1) ; it is easily checked that

(1) A2 and A3 = 0 BB BB BB BB BB

@

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 CC CC CC CC CC A

have safe symbols.

(2) there exists

0 = 1; 1 = 4; 2 = 1 and

s2 = b14; s3 = b14b41= s2b41

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

4.4 Conclusion

In the section we describe some Remarks and examples related to the prim-itivity of An:

Remark 21 For the examples in the section4.3; we can …nd all cases for H2 and V2 which satisfying the Theorem5.8 related to the extensively weak mixing property in [33] can all let An be primitive for all n 2: Therefore, we can cover the Theorem5.8 in [33], i.e., the Theorem12 in our paper can be used to show more examples that An is primitive therein for all n 2 than the Theorem5.8 in [33].

Remark 22 Observing the examples in the section4.3; we …nd one of H and V 2 1 1

1 1 ; 1 1

1 0 ; 0 1

1 1 ;

In fact, if H and V satisfy one of the follow situations, and using the intro-duced method to get H2 and V2; then for A2 = one of H2 and V2; Theorem12 is applied to show that An is primitive for all n 2:

(1) one of H and V = E; and the other =2 fOg ;

(2) one of H and V = G; and the other 2 fU; L; I; T1; T2; K1g ; (3) one of H and V = G0; and the other 2 fU; L; I; T3; T4; K4g ;

(4) one of H and V 2 fU; L; Ig ; and the other 2 fK1; K2; K3; K4g ; Next, we give one example to show the statement given above.

Example 23 (from(1)) If

H = E = 1 1

By (2:1) ; it is easily checked that

(1) A2 and A3 =

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

Remark 24 If A2 is not constructed from H and V; then Theorem12 is also applied to show that An is primitive for all n 2:

we give one example follow.

Example 25 (Simpli…ed Golden Mean) Consider

A2 =

By (2:1) ; it is easily checked that

(1) A2 and A3 =

and

s2 = b11; s3 = b11b11= s2b11

such that (2)-(a)~(2)-(c) of Theorem12 hold, then Theorem12 is applied to show that An is primitive for all n 2:

References

[1] J. Bell, Some threshold results for modes of myelinated nerves, Math.

Biosci., 54(1981), pp. 181-190.

[2] R. Bellman, Introduction to matrix analysis, Mc Graw-Hill, N. Y.

(1970).

[3] J. Bell and C. Cosner, Threshold behavior and propagation for nonlinear di¤erential-di¤erence systems motivated by modeling myelinated axons, Quart. Appl. Math., 42(1984), pp. 1-14.

[4] P. W. Bates and A. Chmaj, A discrete convolution model for phase transitions, Arch. Rat. Mech. Anal, 150(1999), pp. 281-305.

[5] J. C. Ban, K. P. Chien and S. S. Lin, Spatial disorder of CNN-with asymmetric output function, International J. of Bifurcation and Chaos, 11(2001), pp. 2085-2095.

[6] J. C. Ban, C. H. Hsu and S. S. Lin, Spatial disorder of Cellular Neural Network-with biased term, International J. of Bifurcation and Chaos, 12(2002), pp. 525-534.

[7] J. C. Ban and S. S. Lin Patterns Generation and Transition Matrices in Multi-Dimensional Lattice Models, submitted (2002):

[8] J. C. Ban, S. S. Lin and Y. H. Lin, Su¢ cient condition for the mixing property of 2-dimensional subshift of …nite type, preprint (2005).

[9] J. C. Ban, S. S. Lin and C. W. Shih, Exact number of mosaic patterns in cellular neural networks, International J. of Bifurcation and Chaos, 11(2001), pp. 1645-1653.

[10] P. W. Bates, K. Lu and B. Wang, Attractors for lattice dynamical sys-tems, International J. of Bifurcation and Chaos, 11(2001), pp. 143-153.

[11] L. O. Chua, CNN: A paradigm for complexity. World Scienti…c Series on Nonlinear Science, Series A, 31. World Scieti…c, Singapore.(1998) [12] J. W. Cahn, Theory of crystal growth and interface motion in crystalline

materials, Acta Metallurgica, 8(1960), pp. 554-562.

[13] L. O. Chua, K. R. Crounse, M. Hasler and P. Thiran, Pattern formation properties of autonomous cellular neural networks, IEEE Trans. Circuits Systems, 42(1995), pp. 757-774.

[14] H. E. Cook, D. De Fontaine and J. E. Hilliard, A model for di¤usion on cubic lattices and its application to the early stages of ordering, Acta Metallurgica, 17(1969), pp. 765-773.

[15] S. N. Chow and J. Mallet-Paret, Pattern formation and spatial chaos in lattice dynamical systems II, IEEE Trans. Circuits Systems, 42(1995), pp. 752-756.

[16] S. N. Chow, J. Mallet-Paret and E. S. Van Vleck, Dynamics of lattice dif-ferential equations, International J. of Bifurcation and Chaos, 9(1996), pp. 1605-1621.

[17] S. N. Chow, J. Mallet-Paret and E. S. Van Vleck, Pattern formation and spatial chaos in spatially discrete evolution equations, Random Comput.

Dynam., 4(1996), pp. 109-178.

[18] L. O. Chua and T. Roska, The CNN paradigm, IEEE Trans. Circuits Systems, 40(1993), pp. 147-156.

[19] S. N. Chow and W. Shen, Dynamics in a discrete Nagumo equation:

Spatial topological chaos, SIAM J. Appl. Math, 55(1995), pp. 1764-1781.

[20] L. O. Chua and L. Yang, Cellular neural networks: Theory, IEEE Trans.

Circuits Systems, 35(1988), pp. 1257-1272.

[21] L. O. Chua and L. Yang, Cellular neural networks: Applications, IEEE Trans. Circuits Systems, 35(1988), pp. 1273-1290.

[22] G. B. Ermentrout, Stable periodic solutions to discrete and continuum arrays of weakly coupled nonlinear oscillators, SIAM J. Appl. Math., 52(1992), pp. 1665-1687.

[23] T. Eveneux and J. P. Laplante, Propagation failure in arrays of coupled bistable chemical reactors, J. Phys. Chem., 96(1992), pp. 4931-4934.

[24] G. B. Ermentrout and N. Kopell, Inhibition-produced patterning in chains of coupled nonlinear oscillators, SIAM J. APPL. Math., 54(1994), pp. 478-507.

[25] G. B. Ermentrout, N. Kopell and T. L. Williams, On chains of oscillators forced at one end, SIAM J. Appl. Math., 51(1991), pp. 1397-1417.

[26] W. J. Firth, Optical memory and spatial chaos, Phys. Rev. Lett., 61(1988), pp. 329-332.

[27] M. Hillert, A solid-solution model for inhomogeneous systems, Acta Met-allurgica, 9(1961), pp. 525-535.

[28] J. P. Keener, Propagation and its failure in coupled systems of discrete excitable cells, SIAM J. Appl. Math., 47(1987), pp. 556-572.

[29] J. P. Keener, The e¤ects of discrete gap junction coupling on propagation in myocardium, J. Theor. Biol., 148(1991), pp. 49-82.

[30] A. L. Kimball, A. Varghese and R. L. Winslow, Simulating cardiac si-nus and atrial network dynamics on the connection machine, Phys. D, 64(1993), pp. 281-298.

[31] D. Lind and B. Marcus, An introduction to symbolic dynamics and coding, Cambrige University Press, New York, 1995.

[32] J. Mallet-Paret and S. N. Chow, Pattern formation and spatial chaos in lattice dynamical systems I, IEEE Trans. Circuits Systems, 42(1995), pp. 746-751.

[33] N. G. Markley and M. E. Paul, Matrix subshifts for Zv symbolic dy-namics, to be published in Proceedings of the London Mathematical Society.

[34] N. G. Markley and M. E. Paul, Maximal measures and entropy for Zv subshifts of …nite type.

[35] R. S. Mackay and J. A. Sepulchre, Multistability in networks of weakly coupled bistable units, Phys. D, 82(1995), pp. 243-254.

[36] W. Shen, Lifted lattices, hyperbolic structures, and topological disorders in coupled map lattices, SIAM J. Appl. Math, 56(1996), 1379-1399.

相關文件