readme

README.md

@@ -5,7 +5,7 @@ This semester project (SP) focuses on the prediction of parameters of sinusoidal
 As part of this assignment, implement in PyTorch a minGRU architecture following the specifications from [Popov et al. (2023)](https://arxiv.org/abs/2410.01201).
 Consider the simple periodic function:
-\[ y_i(A_i, \omega_i; t) = A_i \sin(\omega_i t) \]
+$$ y_i(A_i, \omega_i; t) = A_i \sin(\omega_i t) $$
 where \( A \) represents the amplitude, \( \omega \) the frequency, and \( t \) is the time variable.
 Restrict the time variable to the interval \( t \in [0, 2\pi] \).
@@ -23,4 +23,4 @@ The dataset required for this project is generated programmatically. Therefore,
     jupyter notebook train_noise.ipynb
     ```
-2. The results of the training and predictions will be displayed in the respective Jupyter notebooks.
+2. The results of the training and predictions will be displayed in the respective Jupyter notebooks.
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