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There are a couple of things I would suggest: Reshape the input data: It looks to me that you want to analyse a time series if IQ-values and each time series is 128 datapoints. In this case you probably want to treat I and Q as the channels respectively and convolve over ther 128 points. To do this the input data needs to be of shape (128, 2). Right now you ...


There is relatively little data for a deep learning solution - 220 total data points and 20 data points for each of the 11 labels. Increasing the amount of data would probably have the greatest impact on model performance. The best option would be to collect more data. Another option would be data augmentation.


How to Standardize Image With ImageDataGenerator Standardization is a data scaling technique that assumes that the distribution of the data is Gaussian and shifts the distribution of the data to have a mean of zero and a standard deviation of one. Data with this distribution is referred to as a standard Gaussian. It can be beneficial when training neural ...

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