资源列表
[matlab例程] fit_ML_log_normal
说明： fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!. Given the samples of a laplace distribution, the PDF parameter is found fits data to the probability of the form: p(x) = 1/(2*b)*exp(-abs(x-u)/b)<resident e> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[matlab例程] fit_ML_maxwell
说明： fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*<resident e> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[matlab例程] fit_ML_normal
说明： fit_ML_normal - Maximum Likelihood fit of the normal distribution of i.i.d. samples!. Given the samples of a normal distribution, the PDF parameter is found fits data to the probability of the form: p(r) = sqrt(1/2/pi/sig^2)*exp(-((r-u<resident e> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[matlab例程] fit_ML_rayleigh
说明：fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!. Given the samples of a rayleigh distribution, the PDF parameter is found fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s wit<resident e> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[matlab例程] bayes_classifier
说明：bayesian classifier for 2 cla-bayesian classifier for 2 class<sami> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[matlab例程] naive-bayesian-classifier
说明：naive bayesian classifier in matlab<sami> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[matlab例程] k-means
说明：segmentation is done by k-means algorithm<jayant sogani> 在 2025-06-19 上传 | 大小：1kb | 下载：0
[数学计算/工程计算] erweichazhi
说明：改进二维插值算法，应用并实现，希望对大家有所帮助。-simulated annealing method is the best solution in order to avoid a partial optimization of extreme concern raised by the algorithm to ensure that the final result is that the global optimum, the source Matlab can achieve Ma<ginger> 在 2025-06-19 上传 | 大小：1kb | 下载：0