multi_target

matlab工具箱数学词汇英汉对照表：概率论与数理统计对照等(toolbox matlab mathematics vocabulary of English-Chinese table: Probability Theory and Mathematical Statistics in control, etc.)

一个有趣的人走动程序，很有趣的。。。。。。(One interesting people walking program, very interesting. . . . . .)

计算任意一个矩阵的模最大最小值。在matlab的m文件编程，实现(Any calculation of maximum and minimum modulus of a matrix. M-file in matlab programming,)

It s the Gabor filter using in Gist impelementation.

POCS算法实现，较为全面，使用的一个程序。 (POCS algorithm)

二次规划法用拉格朗日方法求解等式约束二次规划和用有效集方法解一般约束二次规划问题(Quadratic Programming Lagrangian method for solving equality constrained quadratic programming and the use of efficient collection method for solving general constrained quadratic programming problems)

用于数据集的过采样处理，其中含有一个实例，可以参考。(Oversampling Processing for Data Sets,and it have a sample for study.)

经典语音降噪算法，提高语音信号信噪比和语音可读性，谱减法源代码(Classic voice noise reduction algorithms to improve the readability of signal-to-noise ratio and the voice of the voice signal to spectral subtraction source code)

小电流接地系统发生接地故障时，利用prony算法提取暂态特征分量并利用相关分析法实现选线取得很好的效果，有效的排除了干扰信号的影响，结论明显、准确性高。(When the small current grounding system occurs ground fault , we use prony algorithm to extract the transient characteristics of the component and line selection by using correlation analysis. The simulation present that the algorithm effectively eliminate the influence of interfering signal. The result has a good effect and high accuracy obviously.)

OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.