Physical Neural Network

What Does Physical Neural Network Mean?

A physical neural network is a type of neural network in which the activity of individual artificial neurons is modeled, not by a software program, but by actual physical materials. These systems are based much more concretely on the biophysical processes of the human brain, and are a very specific and sophisticated type of neural network that is not extremely common in the tech world.


Techopedia Explains Physical Neural Network

Because it is so much easier to build a neural network on a software model, physical neural networks are rare. Some early experiments used electrochemical cells which were called memory resistors or “memristors” to emulate a neuron’s synapse.

In general, the cost and labor-intensive requirements for this model make it an unusual type of neural network. More commonly, the entire structure of the artificial neuron’s synapse is modeled by sets of weighted inputs that engineers can manipulate. Unsurprisingly, though, one of the biggest current physical neural network projects is being developed by DARPA, which often works in the vanguard of new and exciting technologies.


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Margaret Rouse

Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.