[FEATURE] State Transition Network Hysteresis Mode

[jatinchowdhury18]

Implement a hysteresis mode using a state transition network (see, Parker, et. al., 2019).

• Train a model with no parameters
• Implement real-time model with no parameters
• Train and test a model with 1 parameter (saturation)
• Train and test model with all 3 parameters

[jatinchowdhury18]

I've successfully trained an STN with an embedded mapping of the "Drive" parameter, that is ~2.5x more efficient than the NR8 mode. It seems like training with embeddings of the "Saturation" and "Bias" parameters, will be difficult, and even if it can be done, he resulting network will most likely be computationally too expensive.

Instead I'm planning to train STNs for 10 unique "Bias" parameter values and 20 "Saturation" parameter values, and choose the correct network based on the real-time parameter choices.