论文标题
动态系统的马尔可夫模型基于实验数据，用于控制仿生假体的问题
The Markov model of a dynamic system based on experimental data for control problems of bionic prostheses
论文作者
论文摘要
本文专门研究基于延迟空间中马尔可夫链的步态运动学的预测。我们在膝盖和髋关节的矢状平面的角度延迟空间中使用超管网格来构建马尔可夫态。我们的实验信号（从假体的遥测获得）提供了过渡概率。由此产生的马尔可夫模型似乎有助于估计吸引子维度，系统的特征频率等。
This article is devoted to a prediction of gait kinematics based on the Markov chains in the delay space. We use hypercubic grid in the delay space of angles in the sagittal plane in the knee and hip joints to construct Markov states. Our experimental signal (obtained from the telemetry of the prosthesis) provides transition probabilities. The resulting Markov model seems to be helpful for estimation of attractor dimension, characteristic frequencies of the system, and so on.
