Classification of Artificial Neural Networks (ANNs)
There are many types of artificial neural networks (ANN).
Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.[1][2][3][4] Most artificial neural networks bear only some resemblance to their more complex biological counterparts, but are very effective at their intended tasks (e.g. classification or segmentation).
Some artificial neural networks are adaptive systems and are used for example to model populations and environments, which constantly change.
Neural networks can be hardware- (neurons are represented by physical components) or software-based (computer models), and can use a variety of topologies and learning algorithms.
^University Of Southern California (2004-06-16). "Gray Matters: New Clues Into How Neurons Process Information". ScienceDaily. Quote: "... "It's amazing that after a hundred years of modern neuroscience research, we still don't know the basic information processing functions of a neuron," said Bartlett Mel..."
^Weizmann Institute of Science. (2007-04-02). "It's Only A Game Of Chance: Leading Theory Of Perception Called Into Question". ScienceDaily. Quote: "..."Since the 1980s, many neuroscientists believed they possessed the key for finally beginning to understand the workings of the brain. But we have provided strong evidence to suggest that the brain may not encode information using precise patterns of activity."..."
^University Of California – Los Angeles (2004-12-14). "UCLA Neuroscientist Gains Insights Into Human Brain From Study Of Marine Snail". ScienceDaily. Quote: "..."Our work implies that the brain mechanisms for forming these kinds of associations might be extremely similar in snails and higher organisms...We don't fully understand even very simple kinds of learning in these animals."..."
^Yale University (2006-04-13). "Brain Communicates In Analog And Digital Modes Simultaneously". ScienceDaily. Quote: "...McCormick said future investigations and models of neuronal operation in the brain will need to take into account the mixed analog-digital nature of communication. Only with a thorough understanding of this mixed mode of signal transmission will a truly in depth understanding of the brain and its disorders be achieved, he said..."
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