VLSI Implementation of TInMANN
M. Melton, Tan Phan, Doug Reeves, Dave Van den Bout · Neural Information Processing Systems · 1990
A massively parallel, all-digital, stochastic architecture - TInMANN - is described which performs competitive and Kohonen types of learning. A VLSI design is shown for a TInMANN neuron which fits within a small, inexpensive MOSIS TinyChip frame, yet which can be used to build larger networks of several hundred neurons. The neuron operates at a speed of 15 MHz which allows the network to process 290,000 training examples per second. Use of level sensitive scan logic provides the chip with 100% fault coverage, permitting very reliable neural systems to be built.