-
Notifications
You must be signed in to change notification settings - Fork 8
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Create 3 Layer HTM Network for one sensor #2
Comments
Putting this here because even if we have not written the logic for the layers, we can still figure out how to hook up the network. |
In NuPIC we have code that creates the network described above: https://github.com/numenta/htmresearch/blob/master/htmresearch/frameworks/location/location_network_creation.py |
That NuPIC file has great comments and ascii art! |
objects now loaded from the root directory
* changed cache location * pipenv is wonderful * build runs tests and formatters for java/python
We need TM without internal distal synapses. |
Object Pool
Proximal input: sensory layer
Distal input: neighboring object pool layers
Represents: current object
Sensory Layer
Proximal input: sensory feature
Distal input: location from Location Layer / temporal context
Represents: feature at a location in object space
This layer needs to receive distal input in two ways: from itself as in the typical SP/TM operation defined in HTM School, and from the Location Layer. These distal inputs must be mixed.
Location Layer
Proximal input: displacement representing movement
Represents: location in 2D envrionment
When new proximal input representing movement is applied, GCM bumps move from current location to predicted location.
The text was updated successfully, but these errors were encountered: