An Analog VLSI Splining Network
DANIEL B. SCHWARTZ, Vijay K. Samalam · neural information processing systems · 1990
We have produced a VLSI circuit capable of learning to approximate arbitrary smooth of a single variable using a technique closely related to splines. The circuit effectively has 512 knots space on a uniform grid and has full support for learning. The circuit also can be used to approximate multi-variable functions as sum of splines.