Author_Institution :
IBM Res., Yorktown Heights, NY, USA
Abstract :
Summary form only given, as follows. Neural networks have been intensively studied as a discipline in their own right in the last five years (late 1980s, early 1990s). Initial claims were extremely ambitious; by using the brain´s computing principles, networks would eliminate programming, revolutionize computer architecture and sensor interfacing, make analog VLSI a reality, and give guidance to a new understanding of human cognition. Work in two areas is described: statistical methods to deal with classification, prediction, and control in data-rich, intuition-poor problems; and VLSI solutions, both in digital and analog styles, to accommodate these architectures
Keywords :
VLSI; neural nets; parallel architectures; statistical analysis; VLSI solutions; analog VLSI; classification; computer architecture; prediction; sensor interfacing; statistical methods; Analog computers; Biological neural networks; Brain computer interfaces; Cognition; Computer architecture; Computer interfaces; Computer networks; Humans; Neural networks; Very large scale integration;
Conference_Titel :
Computer Design: VLSI in Computers and Processors, 1991. ICCD '91. Proceedings, 1991 IEEE International Conference on