Fix a typo, "see show these" -> see how these in Frequency_Resolution.ipynb

Fix a typo, "see show these" -> see how these in Frequency_Resolution.ipynb

Author: Naereen

Frequency_Resolution.ipynb

@@ -250,7 +250,7 @@
       "\n",
       "Thus, two frequencies that differ by at least this amount should be resolvable in these plots. \n",
       "\n",
-      "Thus, in our last example, we had $f_s= 64,N_s = 128 \\Rightarrow \\delta f = 1/2$ Hz and we were trying to separate two frequencies 0.5 Hz apart so we were right on the edge in this case.  I invite you to download this IPython notebook and try longer or shorter signal durations to see show these plots change. Incidentally, this where some define the notion of *frequency bin* as the DFT resolution ($ f_s/N $) divided by this minimal resolution, $ f_s/N_s $ which gives $ N_s/N $. In other words, the DFT measures frequency in discrete *bins* of minimal resolution, $ N_s/N $.\n",
+      "Thus, in our last example, we had $f_s= 64,N_s = 128 \\Rightarrow \\delta f = 1/2$ Hz and we were trying to separate two frequencies 0.5 Hz apart so we were right on the edge in this case.  I invite you to download this IPython notebook and try longer or shorter signal durations to see how these plots change. Incidentally, this where some define the notion of *frequency bin* as the DFT resolution ($ f_s/N $) divided by this minimal resolution, $ f_s/N_s $ which gives $ N_s/N $. In other words, the DFT measures frequency in discrete *bins* of minimal resolution, $ N_s/N $.\n",
       "\n",
       "However, sampling over a longer duration only helps when the signal frequencies are *stable* over the longer duration. If these frequencies drift during the longer sampling interval or otherwise become contaminated with other signals, then advanced techniques become necessary.\n",
       "\n",
@@ -429,4 +429,4 @@
    "metadata": {}
   }
  ]
-}
+}