matlabli

这是一个关于建立分数布朗信号的Matlab程序。(Create Fractional Brownian Signal.)

regular fuzzy control system

Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. We propose a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis adapts to the data, the reconstruction resolution and signal-to-noise ratio (SNR) is improved compared to a reconstruction with a fixed basis. Moreover, the algorithm automatically masks the particle, thereby separating it from the background. This eliminates the need for ad-hoc filtering or masking in the refinement loop. The algorithm is formulated in a Bayesian maximum-a-posteriori framework and uses an efficient optimization algorithm for the maximization. Evaluations using simulated and actual cryogenic electron microscopy data show resolution and SNR improvements as well as the effective masking of particle from background

说明：  runge现象的matlab仿真，用于数值分析(phenomenon of runge, simulated via matlab, for mathmatical analysis)

该matlab程序实现字母T和L的区分，在9*9格形框里，字母T和L有不同的位置，任意位置，神经网络都可以识别出是T还是L(The program matlab and distinguish letters L, T, in the grid-shaped box 9* 9, the letters L and T have different locations anywhere in the neural network can identify a T or L)

非线性求解的二分法程序，还有非线性方程简单迭代。含误差分析，最大迭代次数。(The dichotomy procedure for nonlinear solutions and the simple iteration of nonlinear equations. The error analysis, the maximum number of iterations.)

车牌识别程序，MATLAB，源代码，M文件(MATLAB)

灰色预测模型,可以做变形监测预测分析，交通控制和预测分析，金融分析(Gray prediction model, deformation monitoring can do predictive analysis, traffic control, and predictive analysis, financial analysis)

最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999. (The newest work tools of svm,it will be very convenient to have it.)

MALTAB 관 련 문 서 -한 글 파 일 입 니 다 .(MALTAB 관 련 문 서-한 글 파 일 입 니 다 .)