基于MATLAB实现的高斯分布函数，将函数图像分成多个高斯函数的波形+使用说明文档.zip

## gmm1 - 1-D Gaussian mixture model toolbox for MATLAB A toolbox for computing with 1-D Gaussian mixture models (gmm1). This code is generally fast but there is space for further improvement (e.g., improved vectorization). #### Contents: - `gmm1cdf.m`: gmm1 cumulative distribution function (cdf) - `gmm1ent.m`: gmm1 differential entropy (numerically estimated) - `gmm1max.m`: Find the global maximum (mode) of gmm1 - `gmm1max_n2.m`: Find the global maximum (mode) of gmm1 with 2 components (faster than `gmm1max.m`) - `gmm1moments.m`: Central moments of gmm1 (mean, variance, skewness, excess kurtosis) - `gmm1pdf.m`: gmm1 probability density function (pdf) - `gmm1prod.m`: Product of two gmm1 - `gmm1rnd.m`: Random draw from gmm1 (not optimal, needs recoding) - `isgmm1.m`: Returns true for a gmm1 struct #### References: This toolbox was created for and extensively used in the following publications (please consider citing them if you use this toolbox): - Acerbi, L., Vijayakumar, S. & Wolpert, D. M. (2014). On the Origins of Suboptimality in Human Probabilistic Inference, *PLoS Computational Biology* 10(6): e1003661. - Acerbi, L., Ma, W. J. & Vijayakumar, S. (2014). A Framework for Testing Identifiability of Bayesian Models of Perception, *Proc. Advances in Neural Information Processing Systems (NIPS ’14)*, Montreal, Canada.