matlab

numerical code for matlab analytical bisec differentiation F FALSEPOS fixedpoint

说明：  DSTBC源码，均可以运行成功，对于在研究DSTBC的朋友会很有帮助，我也希望我能得到其他朋友的帮助，站长手下留情，(DSTBC source can run successfully for the study would be helpful DSTBC friends, I also hope that my other friends can get help, head lenient,)

iris数据集 data形式.可用于matlab(iris data)

可转债论文，研究定价，模型，方法，赎回，回售等(This thesis is devoted to evaluating two-factor convertible bonds. Di® erent zero- coupon bond curves are inputted when evaluating convertible bonds issued by com- panies with di® erent credit ratings. Thus the e® ect of the company s credit on the price of the convertible bond is easily and accurately included during the computa- tion. In the model for the interest rate, the parameters in the variance are determined from the market data by statistics and the market price of risk is determined by a zero-coupon bond curve through solving an inverse problem. When we price the con- vertible bond, a free-boundary problem is solved. A Singularity-Separating Method (SSM) is proposed in order to solve this problem e±ciently. Taking the market data)

基于粒子群算法和遗传算法的PID参数优化程序和相应文档(The Optimization of PID Parameters Based on Particle Swarm Optimization and Genetic Algorithm)

这是一篇大连理工大学的硕士学位论文，题为基于模糊逻辑的多级倒立摆控制系统研究，是在李洪兴教授的指导下完成的。该论文的亮点在于详细的介绍变论域自适应模糊控制思想，并以二级倒立摆为实验对象给出了相应的方针结果。(This is a master' s degree thesis, Dalian University of Technology, entitled Multi-level Fuzzy Logic Inverted Pendulum Control System, is under the guidance of Professor Li Hongxing completed. The paper highlights the detailed description of variable universe adaptive fuzzy control ideas, and to double inverted pendulum as experimental results of the corresponding policy.)

Outlier Detection and Prediction Using Solving Set

format changer - hex to decimal - decimal to hex

基于matlab的有源功率因数校正仿真，含电路仿真图(Matlab-based simulation of active power factor correction, including circuit simulation map)

principal component analysis (PCA ) is a well known approach for dimensionality reduction of the feature space. It has been successfully applied in face recognition. The main idea is to decompose face images into a small set of feature images called eigenfaces, which can be considered as points in a linear subspace called “face space” or “eigenspace”