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计算海水的潜温用新海水状态方程来计算，新海水状态方程(Calculate the potential temperature of sea water equation of state with the new terms, the new equation of state water)

bp 网络逼近函数,作正弦函数逼近.对初学者来说是不错的例子.(bp network approximation functions for sine function approximation. For beginners is a good example.)

通过比较传统仅移相的波束与移相+理想延时的波束，来说明述S波段宽带阵列孔径渡越现象(To demonstrate the aperture effct of S_band windband array, this programe comparing the beam pattern of the traditional beamforming method "phase shifting only" with that of "phase shifting+ ideal delay".)

该文件通过多个实例详细讨论了BP神经网络的原理和应用，希望对你有帮助。(The document discusses the principles and applications of BP neural network through multiple instances. May help to you!)

这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，通过比较概率大小判断一个体重身高二维向量代表的人是男是女，放入决策数组中。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小风险贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。 (This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability conditions, male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector The third step is the application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Bayesian classifier )

matlab中绘图的时候 图形处理的各种技巧 是入门是学习matlab编写m文件用处很大(various techniques in drawing matlab graphics processing time entry is learning to write matlab m file has proved very useful)

pitchn,功能：求一句话的语音基音频率包络。(pitchn matlab)

susan算法 matlab程序 图像边缘提取 分割算法(susan algorithm matlab program image edge extraction segmentation algorithm)

Data sets include far more ancillary information than simple tables of numbers and the DataSet Object (DSO) was designed as a generic container that can hold all of this information. The standard DataSet object is similar to a Matlab structure but it is intended to standardize how data is organized and maintained. It was originally designed in 2000 by a consortium of chemical and engineering industry experts to contain the kinds of data that they worked with in real applications. It has been updated numerous times since then to add relevant functionality needed for multivariate analysis of physical science and engineering data.

MATLAB code for learning purpose