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-rw-r--r--markdown/cheap-frequency-detection6
1 files changed, 3 insertions, 3 deletions
diff --git a/markdown/cheap-frequency-detection b/markdown/cheap-frequency-detection
index 3ad0b82..b284bc2 100644
--- a/markdown/cheap-frequency-detection
+++ b/markdown/cheap-frequency-detection
@@ -303,7 +303,7 @@ then you can use their Pythagorean sum to precisely compute the energy
in that frequency component of the signal.
If you’re dumping the decimated samples into a four-sample circular
-buffer x[0], x[1], x[2], x[3], with some incrementing pointer xp:
+buffer x\[0], x\[1], x[2], x[3], with some incrementing pointer xp:
x[xp++ & 3] = new_sample;
@@ -311,8 +311,8 @@ Then you could imagine using x[xp], x[xp-1], x[xp-2], and x[xp-3] with
the appropriate modulo math. However, this is totally not necessary,
because you actually don’t care how these sinusoids are aligned with
the signal; you only care that they are orthogonal. It’s totally
-valid to compute one phase component as x[0] - x[2] and the other as
-x[1] - x[3] and then compute their Pythagorean sum:
+valid to compute one phase component as x\[0] - x[2] and the other as
+x\[1] - x[3] and then compute their Pythagorean sum:
return pythsum(x[0] - x[2], x[1] - x[3]);