八种最常用的GAN生成式对抗网络代码框架
八种最常用的GAN生成式对抗网络代码框架
Fast DoA estimation of multiple targets using a Denoising Autoencoder and sparse arrays
The realization of k-means clustering algorithm by MATLAB
This program is based on the Adaboost Algorithm and Haar Feature
Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).
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