@article {IOPORT.01525543,
    author       = {Bak{\i}rc{\i}o\u{g}lu, Hakan and Ko\c{c}ak, Ta\c{s}k{\i}n},
    title        = {Survey of random neural network applications.},
    year         = {2000},
    journal      = {European Journal of Operational Research},
    volume       = {126},
    number       = {2},
    issn         = {0377-2217},
    pages        = {319-330},
    publisher    = {Elsevier Science B.V.(North-Holland), Amsterdam},
    doi          = {10.1016/S0377-2217(99)00481-6},
    abstract     = {Summary: This paper consists of a survey of various engineering applications based on the random neural network (RNN) model, and also a summary of the recent image processing techniques such as still image compression, image enlargement, and image fusion. The advantage of the RNN model is that it is closer to biophysical reality and mathematically more tractable than standard neural methods, especially when used as a recurrent structure.},
    identifier   = {01525543},
}