Commit 7d852a91 by Ying-Qiu Zheng

### Update 2021JUL21.md

parent 77f36932
 ... ... @@ -29,7 +29,7 @@ In summary, in addition to finding the the hyper-parameters $\pi, \mu, \Sigma_{ -$\Sigma_{k}^{L} = \frac{1}{N_{k}}\sum_{n=1}^{N}\gamma(y_{nk})(\mathbf{x}^{L}_{n} - \mathbf{\mu}_{k}^{L})(\mathbf{x}^{L}_{n} - \mathbf{\mu}_{k}^{L})^{T}$-$\Sigma_{k}^{H} = \frac{1}{N_{k}}\sum_{n=1}^{N}\gamma(y_{nk})(\mathbf{Ux}^{H}_{n} - \mathbf{\mu}_{k}^{L})(\mathbf{Ux}^{H}_{n} - \mathbf{\mu}_{k}^{L})^{T}$-$\pi_k = \frac{N_{k}}{N}$-$\mathbf{U}=$-$\mathbf{U}=\mathbf{MN}^{T}$where$\mathbf{MDN}^{T}$is the svd of$\sum_{k=1}^{K}\gamma(y_nk)\mu_{k}^{L}(\mathbf{x}_{n}^{H})^{T}(\sum_{n=1}^{N}\mathbf{x}_{n}^{H}(\mathbf{x}_{n}^{H})^{T})$- Evaluate the likelihood and check for convergence. 5. Using$\mu_{k}^{L}, \Sigma_{k}^{L}, \pi_{k}`\$ to assignment unseen low-quality data points. ... ...
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