Merge branch 'master' of github.com:unpingco/Python-for-Signal-Processing

Author: unpingco

Expectation_Maximization.ipynb

@@ -231,11 +231,11 @@
       "\n",
       "by maximizing it using basic calculus. The trick is to remember that $\\hat{z}_i$ is *fixed*, so we only have to maximize the $\\log$ parts. This leads to\n",
       "\n",
-      "$$ \\hat{\\mu}_a = \\frac{\\sum_{i=1}^n \\hat{z}_i x_i}{\\sum_{i=1}^n  \\hat{z}_i } $$\n",
+      "$$ \\hat{\\mu_a} = \\frac{\\sum_{i=1}^n \\hat{z}_i x_i}{\\sum_{i=1}^n  \\hat{z}_i } $$\n",
       "\n",
       "and for $\\mu_b$ \n",
       "\n",
-      "$$ \\hat{\\mu}_b = \\frac{\\sum_{i=1}^n (1-\\hat{z}_i) x_i}{\\sum_{i=1}^n  1-\\hat{z}_i } $$\n",
+      "$$ \\hat{\\mu_b} = \\frac{\\sum_{i=1}^n (1-\\hat{z}_i) x_i}{\\sum_{i=1}^n  1-\\hat{z}_i } $$\n",
       "\n",
       "Now, we finally have the *maximization* step ( above ) and the *expectation* step ($\\hat{z}_i$) from earlier. We're ready to simulate the algorithm and plot its performance!\n"
      ]