A threshold function changes its value sharply when its input reaches a particular value (the threshold). The simplest is a step function from zero (or –1) when it input is less than zero to 1 thereafter. A hard threshold is simple to implement, but can inhibt learning; so neural networks typcally use a non-linear sigmoid function instead.
Used in Chap. 6: pages 75, 76
Also known as thresholding function
Step threshold function
Sigmoid threshold function