83050_M1

在MATLAB开发平台上，在做图像的处理进行分割时，可采用迭代法求阈值进行分割。(In the MATLAB development platform to do image processing in the segmentation, the iterative method can be used to segment the threshold requirements.)

Applied Numerical Methods MATLAB Files

读取地震数据的重要模块，这里包含了segy与su文件格式的文件读写还有一些基本的设置模块，非常强大和实用。具有独立性的模块，便于携带和复制！(Read seismic data module, file read and write segy su file format, there are some basic settings module is very powerful and practical. The independence of the modules, easy to carry and copy!)

PSK系统半解析仿真 matlab符号间干扰ISI与误码率的关系 与Eb/No的对应关系(Correspondence between PSK system semi-analytical simulation matlab inter-symbol interference ISI and BER with Eb/No)

说明：  可根据所给参数绘制出头模型图形，并对其进行投影和反投影重建的算法，可正常运行，得到较为理想的结果。(Can be drawn according to the parameters of his early model of graphics, and its projection and back projection reconstruction algorithm, running, get more desirable results.)

使用matlab查询日期的方法，有需要的看看。(The date of the use of matlab query methods, there is a need to look at.)

关于pso的相关源代码，注释详细，可供参考(About the pso relevant source code, comments detailed. )

MULTIDIMENSIONAL SCALING in matlab by Mark Steyvers 1999 ％needs optimization toolbox ％Modified by Bruce Land ％--Data via globals to anaylsis programs ％--3D plotting with color coded groups ％--Mapping of MDS space to spike train temporal profiles as described in ％Aronov, et.al. "Neural coding of spatial phase in V1 of the Macaque" in ％press J. Neurophysiology(MULTIDIMENSIONAL SCALING in Matlab by Mar 1999% k Steyvers needs optimization toolbox% M odified by Bruce Land%-- Data via globals to ana ylsis programs%-- 3D plotting with color coded groups%-- Mapping of MDS space to spike train te mporal profiles as described in% Aronov, et.al. "Neural coding of spatial phase in V1 of t he Macaque "in press J. Neurophysiology%)

克里金法广泛地应用于地下水模拟、土壤制图等领域，是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布．确定对一个待插点值有影响的距离范围，然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后，为达到线性、无偏和最小估计方差的估计，而对每一个样品赋与一定的系数，最后　进行加权平均来估计块段品位的方法。(Kriging is a technique that provides the Best Linear Unbiased Estimator of the unknown fields (Journel and Huijbregts, 1978 Kitanidis, 1997). It is a local estimator that can provide the interpolation and extrapolation of the originally sparsely sampled data that are assumed to be reasonably characterized by the Intrinsic Statistical Model (ISM). An ISM does not require the quantity of interest to be stationary, i.e. its mean and standard deviation are independent of position, but rather that its covariance function depends on the separation of two data points)

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