Search Result for "neuron": 
Wordnet 3.0

NOUN (1)

1. a cell that is specialized to conduct nerve impulses;
[syn: nerve cell, neuron]


The Collaborative International Dictionary of English v.0.48:

Neuron \Neu"ron\, n.; pl. Neura. [NL., from Gr. ney^ron nerve.] (Anat.) 1. The brain and spinal cord; the cerebro-spinal axis; myelencephalon. [obsolete] --B. G. Wilder. [1913 Webster] 2. (Cell Biology) The characteristic specialized cell that is part of the nervous system, serving to conduct electrical impulses to and from the brain, and also between other parts of the body, and composed of a main cell body, the axon, with a varying number of processes of varying length, the dendrites; a nerve cell. The movement and behavior of higher animals depends on the signals tranmsitted by such nerve cells. [PJC]
WordNet (r) 3.0 (2006):

neuron n 1: a cell that is specialized to conduct nerve impulses [syn: nerve cell, neuron]
Moby Thesaurus II by Grady Ward, 1.0:

27 Moby Thesaurus words for "neuron": afferent neuron, autonomic nervous system, axon, brain, central nervous system, cerebral cortex, craniosacral nervous system, dendrite, effector organ, efferent neuron, ganglion, gray matter, internuncial neuron, medullary sheath, nerve, nerve trunk, nervous system, peripheral nervous system, plexus, sensorium, sensory area, sensory cell, solar plexus, spinal cord, synapse, thoracolumbar nervous system, white matter
The Free On-line Dictionary of Computing (30 December 2018):

artificial neural network neural nets neural network neuron NN (ANN, commonly just "neural network" or "neural net") A network of many very simple processors ("units" or "neurons"), each possibly having a (small amount of) local memory. The units are connected by unidirectional communication channels ("connections"), which carry numeric (as opposed to symbolic) data. The units operate only on their local data and on the inputs they receive via the connections. A neural network is a processing device, either an algorithm, or actual hardware, whose design was inspired by the design and functioning of animal brains and components thereof. Most neural networks have some sort of "training" rule whereby the weights of connections are adjusted on the basis of presented patterns. In other words, neural networks "learn" from examples, just like children learn to recognise dogs from examples of dogs, and exhibit some structural capability for generalisation. Neurons are often elementary non-linear signal processors (in the limit they are simple threshold discriminators). Another feature of NNs which distinguishes them from other computing devices is a high degree of interconnection which allows a high degree of parallelism. Further, there is no idle memory containing data and programs, but rather each neuron is pre-programmed and continuously active. The term "neural net" should logically, but in common usage never does, also include biological neural networks, whose elementary structures are far more complicated than the mathematical models used for ANNs. See Aspirin, Hopfield network, McCulloch-Pitts neuron. Usenet newsgroup: news:comp.ai.neural-nets. (1997-10-13)