Class Covariance

                                  object --+        
                                           |        
base.parameterizedobject.ParameterizedObject --+    
                                               |    
                base.functionfamilies.LearningFn --+
                                                   |
                                                  Covariance

Covariance learning rule supporting either input or unit thresholds.

As presented by Dayan and Abbott (2001), covariance rules allow either potentiation or depression of the same synapse, depending on an activity level. By default, this implementation follows Dayan and Abbott equation 8.8, with the unit_threshold determining the level of postsynaptic activity (activity of the target unit), below which LTD (depression) will occur.

If you wish to use an input threshold as in Dayan and Abbott equation 8.9 instead, set unit_threshold to zero and change input_threshold to some positive value instead. When both thresholds are zero this rule degenerates to the standard Hebbian rule.

Requires some form of output_fn normalization for stability.