Photonic neurocomputers and learning machines
N.H. Farhat · 2002
Efforts and progress made towards achieving desirable attributes in analog photonic (optoelectronic and/or electron optical) hardware that utilizes primarily incoherent light are reviewed. A hardware implementation of a stochastic Boltzmann learning machine is used as a vehicle for identifying generic issues and clarifying research and development areas for further advancement of the field. The development of architectures and methodologies for learning in self-organizing networks that employ a type of quasi-nonvolatile storage medium called electron trapping material is discussed.>