change hints.md format (#905)

Author: depial

exercises/practice/fft/.docs/hints.md

@@ -1,15 +1,15 @@
-# Hints
+## General
 
-## 1. DFT
-- This can be done straight from the definition of the DFT: `Xₖ = Σ xₙ * ℯ^(-2iπk * n/N)`
-- While the complexity is fixed at `O(n²)`, there are still methods to do this which are more efficient.
-- Loops are generally slower than matrix multiplication.
+- DFT
+    - This can be done straight from the definition of the DFT: `Xₖ = Σ xₙ * ℯ^(-2iπk * n/N)`
+    - While the complexity is fixed at `O(n²)`, there are still methods to do this which are more efficient.
+    - Loops are generally slower than matrix multiplication.
 
-## 2. FFT
-- As stated in the introduction, this is typically done with a divide-and-conquer strategy, so recursion is likely your friend, but while loops are not ruled out (and can even be more efficient).
-- An outline of an algorithm is as follows:
-    - When the length of the input vector is less than or equal to 1, return the input vector. Otherwise...
-    - The signal is split into two parts, the elements with even indices `Xₑ` and the elements with odd indices `Xₒ`.
-    - The FFT is run on both parts.
-    - The vector `f(n) = ℯ^(-2iπ * n/N)` is made (with `n` running from 0 to N/2-1).
-    - The two parts `Xₑ` and `Xₒ` are recombined into a full vector `[Xₑ + f(n) * Xₒ; Xₑ - f(n) * Xₒ]`, where the addition and multiplications are elementwise.
+- FFT
+    - As stated in the introduction, this is typically done with a divide-and-conquer strategy, so recursion is likely your friend, but while loops are not ruled out (and can even be more efficient).
+    - An outline of an algorithm is as follows:
+        - When the length of the input vector is less than or equal to 1, return the input vector. Otherwise...
+        - The signal is split into two parts, the elements with even indices `Xₑ` and the elements with odd indices `Xₒ`.
+        - The FFT is run on both parts.
+        - The vector `f(n) = ℯ^(-2iπ * n/N)` is made (with `n` running from 0 to N/2-1).
+        - The two parts `Xₑ` and `Xₒ` are recombined into a full vector `[Xₑ + f(n) * Xₒ; Xₑ - f(n) * Xₒ]`, where the addition and multiplications are elementwise.