State transition algorithm (STA) has been emerging as a novel stochastic method for global optimization in recent few years. To make better understanding of continuous STA, a matlab toolbox for continuous STA has been developed. Firstly, the basic principles of continuous STA are briefly described. Then, a matlab implementation of the standard continuous STA is explained, with several instances given to show how to use to the matlab toolbox to minimize an optimization problem with bound constraints. In the same while, a link is provided to download the matlab toolbox via available resources.
On derivative-free extended Kalman filtering and its Matlab-oriented square-root implementations for state estimation in continuous-discrete nonlinear stochastic systems
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
University College London（伦敦大学学院）；RWTH Aachen University（亚琛工业大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
流形上的优化（英语：Optimization on manifold）是一类优化目标函数的方法，在某种意义上说，满足约束的点的集合允许可微流形的结构。虽然许多优化问题的描述的形式，微分几何的技术性和繁琐的计算导数构成了一个显着的障碍，用这些方法进行实验。我们介绍Pymanopt（可在https://pymanopt.github.io上获得），这是一个用Python实现的流形优化工具箱，与Manopt Matlab工具箱类似，它实现了几种流形几何和优化算法。此外，我们通过使用自动微分来计算衍生信息，进一步降低了用户的障碍，节省了用户的时间，并使他们免受潜在的计算和实施错误的影响。
