Hopfield‐type networks: Making the condition of learning pattern more lenient by threshold
Tadashi Aizawa, Akira Hyogo, Keitaro Sekine · Electronics and Communications in Japan (Part III Fundamental Electronic Science) · 1995
Abstract The information storage algorithm of a Hopfield‐type network is a kind of self‐correlation learning. This algorithm needs the condition in which vectors of learning patterns cross at right angles to each other. This paper proposes a method to make this condition easier. To this purpose, threshold is used. An investigation of how to decide quantity is included. This paper discusses a network with units whose state is 1 or 0. Fixing method of threshold has not been proposed before to this type of network. It is, therefore, proposed in this research; the goal is to facilitate learning patterns.