# Alternative Methods to Zero Padding

When using a sequential neural network to classify signals with their frequency spectrum, we would need to normalize the length of the signals to perform vectorization. The only method I'm aware at this point is zero padding. Does zero padding have any disadvantages? If so, are there any alternative methods to that?

$$f_{BW} \approx 1/T$$
Where $$f_{BW}$$ is the equivalent noise bandwidth in Hz (which is the same power that would result from a brickwall filter of that bandwidth if white noise was at the input) and $$T$$ is the duration of the data in seconds.