The design process transforms abstract functional specifications into a manufacturable assembly (or synthesis) of known parts.
Thus far, neural networks have been implemented chiefly as mainframe simulations or in analog array processors (e.g., resistive nets.) Mainframe simulations have the disadvantage of being relative
Three neural net chips will be described. The first is a microfabricated resistor-synapse array with mask-programmed connections.
Rising energy consumption and thus equipment operating cost as well as the parallel environmental need to reduce the carbon footprint is a very important issue in mobile radio networks.
Neural network computing algorithms, which are loosely based on biological models, have been proposed as alternatives to traditional methods for problems in machine perception.
Basic properties of matter will limit the miniaturization of transistors, the basic building block of computers, to dimensions only about ten times smaller than today's most advanced devices.
Basic properties of matter will limit the miniaturization of transistors, the basic building block of computers, to dimensions only about ten times smaller than today's most advanced devices.
This talk reviews work done at Holmdel on designing and building chips that function as electronic neural networks.
We are implementing associative memory circuits based on connectionist models for neural networks.
In the last few years, devices inspired by the architecture of the brain have become much more powerful.
