We need to be able to train Cog actions independant of profiles.
So we could put reliably trained actions together into a user defined profile.
I have a couple of profiles that work very well with some actions, and other profiles that work better with other actions. It would be useful to be able to put all the best trained into one profile.
Especially as those action get refined and changed over time as the user gets better at focussing on them. I have older profiles that worked very well, but now my trigger thoughts have been refined so some actions in teh old profiles don't work. It is a lot of effort to clear and fully retrain those action. It would be much better if I could choose more recent versions fr om a list.
Also this would make it much easier for configuring for specific games. Especially if actions have been trained with specific thoughts relating to a specific game.
A different game may cause those thoughts to be naturally different due to physical differences related to the same type of action.
In which case you would have to create and train a profile for different games.
Far better if you could create a custom profile from existing actions.
We need to be able to deduct overlapping Cog actions that cause false triggers
I have had some success in deducting false triggers from unreliable actions wh ere they overlap.
To do this I experimented with training the nuetral in one profile with the similar action in a second profile (two control panels).
To clarify; an example:
I think left in one profile, it triggers push in the second.
I train neutral in the second profile (push profile) while thinking Left.
This reduces or stops the push being triggered when I think left.
So the nuetral in the second profile becomes an amalgamation of the normal random or quiet nuetral signal and the added left signal. So when I trigger Left, it sees this as part of nuetral, and doesn't false trigger 'push'.
I hope you understand what mean.
It would seem that the training can not only be used to detect and refine the thought pattern recognition. But it could also be used to compare and remove one trained action signal from another.
So if I trained 'Left', but for a few split seconds the signal was the same as 'Push'. The push signal would be included in the left signal as noise.
If I then trained 'Push' (a perfect training)
Whenever I think 'Left', There is a chance it may false trigger 'Push'.
So Left could be trained in a negative way to remove the push noise. Yes?
What I am getting at is, we need a magic button that when pressed, will compare the trained trigger signals. If a hint of one signal is found in another, it could be removed. Similar to dark frame subtraction in astrophotography.
You have a signal that has been trained, you then have a second signal that sometimes cause the first to be false triggered.
So while training increase S/N ratio by dilution of other signals. Deduction of the second signal will remove that noise. or somesuch. It's far too late in the night
LOL, pick the bones out of that
