论文标题
Koopman操作员方法用于计算解决方案结构和非线性有限状态系统的可观察性
Koopman operator approach for computing structure of solutions and Observability of non-linear finite state system
论文作者
论文摘要
给定一个由矢量空间中的映射定义的离散动力系统在有限状态系统(FSS)上定义,使用双映射构建了状态空间函数空间上的双线性系统。该系统构成了动态系统的众所周知的Koopman线性系统框架,因此称为Koopman线性系统(KLS)。首先表明,可以从KLS的溶液中推断出FSS溶液的几种结构特性。非线性FS解决方案结构参数的计算问题在计算上是坚硬的,因此随着变量数量的增加而变得不可行。相比之下,众所周知,这些问题可以通过线性代数来解决线性FSS的基本矩阵及其顺序。在下一步中,KLS被缩小为最小的顺序(称为RO-KLS),同时仍保留了FSS解决方案结构参数的所有信息。因此,当RO-KLS的顺序足够小时,上述非线性FSS的计算问题实际上是可行的。接下来,表明具有输出函数的非线性FSS的可观察性等于具有适当的线性输出映射的RO-KLS的可观察性。因此,通过等效RO-KLS的观察者设计解决了非线性可观察性的问题。这种结构应在密码学和生物网络中产生的现实FSS具有惊人的应用。
Given a discrete dynamical system defined by a map in a vector space over a finite field called Finite State Systems (FSS), a dual linear system over the space of functions on the state space is constructed using the dual map. This system constitutes the well known Koopman linear system framework of dynamical systems, hence called the Koopman linear system (KLS). It is first shown that several structural properties of solutions of the FSS can be inferred from the solutions of the KLS. The problems of computation of structural parameters of solutions of non-linear FSS are computationally hard and hence become infeasible as the number of variables increases. In contrast, it has been well known that these problems can be solved by linear algebra for linear FSS in terms of elementary divisors of matrices and their orders. In the next step, the KLS is reduced to the smallest order (called RO-KLS) while still retaining all the information of the parameters of structure of solutions of the FSS. Hence when the order of the RO-KLS is sufficiently small, the above computational problems of non-linear FSS are practically feasible. Next, it is shown that the observability of the non-linear FSS with an output function is equivalent to that of the RO-KLS with an appropriate linear output map. Hence, the problem of non-linear observability is solved by an observer design for the equivalent RO-KLS. Such a construction should have striking applications to realistic FSS arising in Cryptology and Biological networks.