I have a long time series signal. This signal is usually very stable, but it will change when the sensor is stimulated, and this change is usually very short. I know this can be trained using the labeled method(like neural network ,CNN, etc), but it takes a lot of time to label, this is because my change time is very short(about 4 seconds), and the change time is not much. So, I want to generate a number of signals similar to patterns using random numbers, and then use an autoencoder(or feature extraction method) to learn features before performing detection.
What I want to ask is if there are any errors in my ideas or can anyone provide some ideas or opinions. Many thank!