An Analog VLSI Splining Network
Abstract
We have produced a VLSI circuit capable of learning to approximate ar(cid:173) bitrary 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.
Cite
Text
Schwartz and Samalam. "An Analog VLSI Splining Network." Neural Information Processing Systems, 1990.Markdown
[Schwartz and Samalam. "An Analog VLSI Splining Network." Neural Information Processing Systems, 1990.](https://mlanthology.org/neurips/1990/schwartz1990neurips-analog/)BibTeX
@inproceedings{schwartz1990neurips-analog,
title = {{An Analog VLSI Splining Network}},
author = {Schwartz, Daniel B. and Samalam, Vijay K.},
booktitle = {Neural Information Processing Systems},
year = {1990},
pages = {1008-1014},
url = {https://mlanthology.org/neurips/1990/schwartz1990neurips-analog/}
}