Abstract
The construction of a hierarchical system to distinguish classes of patterns can be improved by the combination of a dynamical elastic matching with a time dependent image resolution. Using the elastic matching as a preprocessing for synergetic computers one achieves an invariant perception by means of arbitrary spatial transformations. On the other hand a time dependent resolution, realized with a Gaussian distribution, can be interpreted as a dynamical change of the available image information. The coupling of these two dynamics results in a hierarchy of locality of pattern transformations. Therefore this system utilizes a dynamical feature extraction and implies the definition several classes of patterns.
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Daffertshofer, A., Haken, H. (1995). Adaptive hierarchical structures. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_159
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DOI: https://doi.org/10.1007/3-540-59497-3_159
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