Show Reference: "Things you haven't heard about the self-organizing map"

Things you haven't heard about the self-organizing map In Neural Networks, 1993., IEEE International Conference on (1993), pp. 1147-1156 vol.3, doi:10.1109/icnn.1993.298719 by T. Kohonen
@inproceedings{kohonen-1993,
    abstract = {The self-organizing map ({SOM}) algorithm can be related to a
biological neural network in many essential known details; even cyclic
behavior automatically ensues from a simple nonlinear neural model,
whereby these cycles correspond to the steps of the discrete-time {SOM}
algorithm. Compared with the other traditional neural-network
algorithms, the {SOM} alone has the advantage of tolerating very low
accuracy in the representation of its signals and synaptic weights. This
is proven by simulations. Such a property ought to be shared by any
realistic neural-network model. While the {SOM} can thus be advanced as a
genuine neural-network paradigm, it is shown how the basic algorithm can
be generalized and made more computationally efficient in several ways},
    author = {Kohonen, T.},
    booktitle = {Neural Networks, 1993., IEEE International Conference on},
    doi = {10.1109/icnn.1993.298719},
    institution = {Lab. of Comput. \& Inf. Sci., Helsinki Univ. of Technol., Espoo},
    isbn = {0-7803-0999-5},
    keywords = {ann, biology, learning, math, som, unsupervised-learning},
    pages = {1147--1156 vol.3},
    posted-at = {2011-12-12 10:57:49},
    priority = {2},
    publisher = {IEEE},
    title = {Things you haven't heard about the self-organizing map},
    url = {http://dx.doi.org/10.1109/icnn.1993.298719},
    year = {1993}
}

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