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surface counter for matlab

MATLAB编写的ARMA建模程序，可实现UI打开EXCEL文件，自动选取合适滞后阶数ARMA建模和任意几期预测。(ARMA modeling program written in MATLAB, enabling the UI Open EXCEL file and automatically selects the appropriate number of lags several of ARMA modeling and forecasting arbitrary.)

Self-advising support vectore machine

matlab下数字信号处理实现实例，对初学者很说是很好的教材，包括源码实现(digital signal processing under matlab realize examples, for beginners it is good teaching materials, including source code to achieve)

发个大集合，有线性阵列，圆形阵列，矩形阵列，极坐标等(Send a large collection, there is a linear array, circular array, rectangular array, polar coordinates)

一个粒子群优化算法的实例，对于初步学习者是一个不错的学习实例。(An example of particle swarm optimization algorithm for the initial learner is a good learning example. )

This M-File imports data from binary *.dat files, created with PSpice 6.0 (DOS), 9.1 (Student), and 10.0.3. If you are using newer versions of PSpice, you might need to adjust the code. (This M-File imports data from binary*.dat files, created with PSpice 6.0 (DOS), 9.1 (Student), and 10.0.3. If you are using newer versions of PSpice, you might need to adjust the code. )

：该文把局部三值模式(Local Ternary Patterns, LTP)纹理特征引入Mean Shift 跟踪算法，提出了基于多 特征的Mean Shift 人脸跟踪算法以解决Mean shift 跟踪算法的鲁棒性问题。通过对LTP 纹理特征的分析、研究， 提出了一个LTP 关键纹理模型，既增强了目标的关键纹理信息，又简化了LTP 纹理模型。在此基础上，提出一 种基于LTP 关键纹理特征和肤色特征的Mean Shift 人脸跟踪算法，有效地解决了Mean Shift 算法的鲁棒性问题。 为进一步提高对快速运动目标的跟踪速度和跟踪性能，该文引入了卡尔曼滤波器对目标进行预测。实验结果表明， 该文的算法在目标定位的准确性和跟踪性能上比Mean Shift 算法均有明显的提高。(: In this paper, the texture characteristics of the local ternary patterns Local Ternary Patterns (LTP) Mean Shift tracking algorithm proposed Mean Shift face tracking algorithm based on multiple features in order to solve the Mean shift tracking algorithm robustness. Texture characteristics of LTP analysis, research, a key LTP texture model, not only enhanced the key goal of texture information, but also simplifies the the LTP texture model. On this basis, based on the LTP key texture features and color characteristics Mean Shift face tracking algorithm, effectively solved the robustness of the Mean Shift algorithm. To further enhance the fast-moving target tracking speed and tracking performance, this paper introduces the Kalman filter to predict the target. The experimental results show that the algorithm of the text in the target positioning accuracy and tracking performance than the Mean Shift algorithm to significantly improve.)

the action of denoiszing the actual noise from an system

MATLAB调用COM，源代码，很好用，非常不错(MATLAB calls COM, source code, very good, very good)