测地线
下降(航空)
李雅普诺夫函数
数学
梯度下降
算法
应用数学
计算机科学
数学分析
物理
人工智能
非线性系统
量子力学
气象学
人工神经网络
出处
期刊:Journal of Computational Mathematics
[Global Science Press]
日期:2014-06-01
卷期号:32 (1): 93-106
被引量:5
标识
DOI:10.4208/jcm.1310-m4225
摘要
A new framework based on the curved Riemannian manifold is proposed to calculate the numerical solution of the Lyapunov matrix equation by using a natural gradient descent algorithm and taking the geodesic distance as the objective function.Moreover, a gradient descent algorithm based on the classical Euclidean distance is provided to compare with this natural gradient descent algorithm.Furthermore, the behaviors of two proposed algorithms and the conventional modified conjugate gradient algorithm are compared and demonstrated by two simulation examples.By comparison, it is shown that the convergence speed of the natural gradient descent algorithm is faster than both of the gradient descent algorithm and the conventional modified conjugate gradient algorithm in solving the Lyapunov equation.
科研通智能强力驱动
Strongly Powered by AbleSci AI