Rapid Feature Extraction via the Radon Transform.
Final rept. 1 Oct 85-1 Dec 87,
YALE UNIV NEW HAVEN CONN
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The investigators explored the area of neural-net associative memories and their optical implementations. The problem of organizing an associative memory to reflect known structure in the pattern is addressed because the structure is encoded as a model in the memory, the memory differs considerably from simple pattern matchers where an iconic version of the pattern is stored. Early work concentrated on the idea of encoding a compositional hierarchy within the memory. Though this worked well, the theory was inadequate to explain the behavior of the memory. An optimization approach was adopted in which the goal of the computation could be stated in a mathematical objective function. The ideas of compositional and inheritance hierarchies were encoded directly into the objective function. A simulator was completed that demonstrated these ideas. Optical implementation was concerned with the problem of implementing ever more general interconnect patterns. The investigators began with the construction of a system that computed Radon Transforms of the input object. This demonstrated the necessary first step of an optical connection scheme to transform objects to parameter spaces. A more complex system was built that demonstrated discrete space-invariant connection patterns. This worked satisfactorily. The current work involves designs for holographic space-variant connection patterns.
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