matlab-Surface

matlab的全英文书籍，用于更好的理解和编写matlab原编码，希望有帮助(matlab full English books, to better understand and prepare for the matlab source code, hope that helps)

matlab应用大全-赵海滨，第9章反馈神经网络源码(matlab application Daquan- ZhaoHaiBin Chapter 9 feedback neural network source)

说明：  神经网络的综合基础的试验文件，用于数学建模中的神经网路算法(Integrated neural network based test file)

说明：  先进pid控制matlab仿真（第二版） 1、所有仿真算法按章归类，光盘中的程序名与书中一一对应。 2、将光盘中的仿真程序复制到硬盘MATLAB运行的路径中，便可仿真运行。 3、本书算法在MATLAB 5.3版下运行成功，并适用于其他版本。 4、程序chap1_11.mdl；chap3_2.mdl；chap3_5.mdl；chap6_2.mdl；chap6_4.mdl需要在Matlab6.5下运行，特此说明。 5、假如您对仿真程序有疑问，请及时通过 E-mail 与作者联系。 北京航空航天大学 刘金琨 E-mail 地址： ljk@dept3.buaa.edu.cn或ljk@buaa.edu.cn (advanced pid control Matlab simulation (2nd Edition) 1, all simulation algorithm grouped by chapter, the CD-ROM from the procedure he gathers with the book. Two of the CD-ROM simulation program MATLAB copied to the hard drive running in the path, the simulation can be run. 3, the book algorithm in MATLAB 5.3 version running success, and applicable to other versions. 4, procedures chap1_11.mdl; Chap3_2.mdl; Chap3_5.mdl; Chap6_2.mdl; Chap6_4.mdl need Matlab6.5 running, it is noted. Five, if you are right simulation program have queries, please timely adoption of E-mail contact with the author. Beijing University, Hangzhou aviation space E-mail address : ljk@dept3.buaa.edu.cn or ljk@buaa.edu.cn)

PLL basic modal in simulink

说明：  Matlab编写的深度学习，DBN深度信念神经网络(Matlab preparation of deep learning, DBN deep belief neural network)

MATLAB implementation of time series prediction Based on the VQTAM method described in the following papers: G. A. Barreto & A. F. R. Araujo (2004) "Identification and Control of Dynamical Systems Using the Self-Organizing Map" IEEE Transactions on Neural Networks, vol. 15, no. 5.

共轭梯度法是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。(Conjugate gradient method is between the steepest descent method and Newton method between a method that only use the first derivative information, but the steepest descent method to overcome the disadvantage of slow convergence, but also avoids the need to store and calculate Newton Hesse matrix and the shortcomings of the inverse, conjugate gradient method is not only linear equations to solve large-scale one of the most useful, large-scale nonlinear optimization solution is also the most efficient algorithms.)

Solar Charge Controller

fdtd_2d basic algorithum version 1 isotopic linear non-dispersive material an soft gaussian source Dirichlet boundary conditions grid size and time size is designated directly Ez mode electic field nomalized