Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System

Figure 7

Change of each map during learning process. Left maps show Feature Maps and Right maps show Action Maps in (a)–(d). Comparing the learning result showed by (c) and (d), it is easy to find that except of the action “1”, PL-G-SOM showed to be more effective in gathering the similar input on its Action Map as neighbored output comparing with T-SOM.

(a) T-SOM: $t=0$

(b) PL-G-SOM: $t=0$

(c) T-SOM: $t=300$

(d) PL-G-SOM: $t=300$