As usual, CC training begins in an output phase with no hidden units. But with the encoder option, the only available weights are from the bias unit. Trainable connection weights are drawn in this slideshow as dashed arrows. Initially, the weights have random values, generating random performance. Weights are adjusted to reduce discrepancy (error) between the input and output vectors. Error reduction typically stagnates quickly in this first output phase with the encoder option because the network is taking no account of variation in input patterns.
The bias unit always has an input activation of 1.0, regardless of the input pattern being presented. With trainable connection weights to all downstream units, the bias unit implements a learnable resting activation level for each downstream unit.