I am working on the epilepsy classification system which consumes EEG signals and in the result says if withing the certain period is a seizure or not. I take an advantage of Keras API for the sake of network training. I am giving a try at a few different neural network configurations and now I wonder is it possible that MLP is better than CNN in 1D classification in some cases? My question is not only related to EEG or epilepsy detection, but more if there is any example when MLP behaves better than CNN in the sense of accuracy. Or maybe it is mathematically proven that there is always some CNN which will beat MLP for the given classification problem.
For CNN I use
keras.layers.Conv1D, for MLP
keras.layers.Dense if that matters.