Reorganizing

Cleaned up folders

With 1000 training images, and 100 epochs, the trained model is able to reconstruct the images fairly well

Set up initialization of epoch runs

Created recontrain to implement model reconstruction after the decoder has been trained

Cleaned files

Updated number of iterations

Created reconstruction file

Added a way to track the average max and min update over iterations

feat(training): Implemented STDP Weight Update, Model is Converging

Implemented spikegen using 1/x encoding of intensity to latency

Rewriting

Rewriting signfiicant parts of the code

Testing reconstruction

Cleaned stdp_time.py