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In the paper, the mixing property of ℤ2 subshift of finite type (SFT) is studied, some checkable conditions are provided to examine the property of mixing. Once the mixing property is checked, a class of examples can be found to show it possesses an entropy conjugacy property proposed in [Quas & Trow, 2000]. Finally, we construct an example of two shift spaces X and Y that are entropy conjugate but not conjugate.

This work investigates the dissipative dynamical system in the infinite lattice ℤ. The dynamics of each node depends on itself and nearby nodes by a nonlinear function. When each node is perturbed with weighted Gaussian white noise, a unique pullback attractor and forward attractor exists whose domain of attraction are random tempered sets. Furthermore, we prove that the pullback and forward attractors are equivalent to a random equilibrium which is also tempered. Both convergence to the pullback and forward attractors are exponentially fast.

This study investigates the complexity of the global set of output patterns for one-dimensional multi-layer cellular neural networks with input. Applying labeling to the output space produces a sofic shift space. Two invariants, namely spatial entropy and dynamical zeta function, can be exactly computed by studying the induced sofic shift space. This study gives sofic shift a realization through a realistic model. Furthermore, a new phenomenon, the broken of symmetry of entropy, is discovered in multi-layer cellular neural networks with input.

The degree of mixing is a fundamental property of a dynamical system. General multi-dimensional shifts cannot be systematically determined. This work introduces constructive and systematic methods for verifying the degree of mixing, from topological mixing to strong specification (or strong irreducibility) for two-dimensional shifts of finite type. First, transition matrices on infinite strips of width $n$ are introduced for all $n\geq 2$. To determine the primitivity of the transition matrices, connecting operators are introduced to reduce the order of high-order transition matrices to yield lower-order transition matrices. Two sufficient conditions for primitivity are provided; they are invariant diagonal cycles and primitive commutative cycles of connecting operators. After primitivity is established, the corner-extendability and crisscross-extendability are used to demonstrate topological mixing. In addition, the hole-filling condition yields the strong specification. All mentioned conditions can be verified to apply in a finite number of steps.

This talk is concerned with zeta functions of two-dimensional shifts of finite type. The zeta function is an important invariant, which combines information of all periodic patterns. The zeta function can be explicitly expressed as a reciprocal of an infinite product of polynomials by patterns generation approaches. The methods can apply to two-dimensional cellular neural networks.