In a perceptron, let inputs be $0$ or $1.$ Let the output be y $=0$ or $1,$ and the correct

output be C$.$ The Perceptron Learning Rule can be summarised as:

$1.$ If y$=0$ and C$=1,$ then reduce threshold and reduce weights.

$2.$ If y$=1$ and C$=0,$ then increase threshold and increase weights.

$3.$ If y$=0$ and C$=1,$ then reduce threshold and increase weights.

$4.$ If y$=1$ and C$=0,$ then reduce threshold and increase weights.

$5.$ If y$=0$ and C$=1,$ then increase threshold and reduce weights.