Recurrent Neural Network: TimeDelay Neural Network Implemented in Fast Compressed Neural Network For R
This a general overview of how a time delay network data flow would work. Note that I've ommited the actual weight calculations/tuning etc. and I've generally skipped the hidden layer calculations and shown only a 2X time delay. In theory you can show X time delays b
Red are the current set of inputs
Blue are the outputs from the previous evaluation
Green are the outputs from the run before that. etc. etc.
Purple is the hidden layer
Teal is the output layer
Code coming soon.
General flow is this.
In the diagram above. Data consists of a time series with four inputs, doesn't matter what.
Height, Weight, Length, Width
Outputs are what we are attempting to predict/react to. Lets say BASE 10 output: Up, Down, Left, Right
Time series data would look something like this:
So Values for the input nodes on the first run:
So Values for the input nodes on the Second run: