Introducing quantum convolutional neural networks

Machine learning techniques have so far proved to be very promising for the analysis of data in several fields, with many potential applications. However, researchers have found that applying these methods to quantum physics ...

Organized chaos gets robots going (Update)

(PhysOrg.com) -- Even simple insects can generate quite different movement patterns with their six legs. The animal uses various gaits depending on whether it crawls uphill or downhill, slowly or fast. Scientists from Gottingen ...

page 1 from 7

Biological neural network

In neuroscience, a neural network describes a population of physically interconnected neurons or a group of disparate neurons whose inputs or signalling targets define a recognizable circuit. Communication between neurons often involves an electrochemical process. The interface through which they interact with surrounding neurons usually consists of several dendrites (input connections), which are connected via synapses to other neurons, and one axon (output connection). If the sum of the input signals surpasses a certain threshold, the neuron sends an action potential (AP) at the axon hillock and transmits this electrical signal along the axon.

In contrast, a neuronal circuit is a functional entity of interconnected neurons that influence each other (similar to a control loop in cybernetics).

This text uses material from Wikipedia, licensed under CC BY-SA