Optical neural network
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An optical neural network is a physical implementation of an artificial neural network with optical components.
Some artificial neural networks that have been implemented as optical neural networks include the Hopfield neural network[1][2] and the Kohonen self-organizing map with liquid crystals [3].
Biological neural networks function on an electrochemical basis, while optical neural networks use electromagnetic waves. Optical interfaces to biological neural networks can be created with optogenetics, but is not the same as an optical neural networks. In biological neural networks there exist a lot of different mechanisms for dynamically changing the state of the neurons, these include short-term and long-term synaptic plasticity. Synaptic plasticity is among the electrophysiological phenomena used to control the efficiency of synaptic transmission, long-term for learning and memory, and short-term for short transient changes in synaptic transmission efficiency. Implementing this with optical components is difficult, and ideally requires advanced photonic materials. Properties that might be desirable in photonic materials for optical neural networks include the ability to change their efficiency of transmitting light, based on the intensity of incoming light.
There is one recent (2007) model of Optical Neural Network: the Programmable Optical Array/Analogic Computer (POAC). It had been implemented in the year 2000 and reported based on modified Joint Fourier Transform Correlator (JTC) and Bacteriorhodopsin (BR) as a holographic optical memory. Full parallelism, large array size and the speed of light are three promises offered by POAC to implement an optical CNN. They had been investigated during the last years with their practical limitations and considerations yielding the design of the first portable POAC version.
The practical details: hardware (optical setups) and software (optical templates) are published. However, POAC is a general purpose and programmable array computer that has a wide range of applications including: image processing; pattern recognition; target tracking; real-time video processing; document security; and optical switching.
[edit] External links
- Optical Computing Group, Analogic and Neural Systems Laboratory, Computer and Automation Research Institute, Hungarian Academy of Sciences: http://lab.analogic.sztaki.hu
- Institute for optical neural technologies (Russian Academy of Sciences): http://www.iont.ru
