With the basic components described in the last chapters — interconnection and storage devices in chapter 4 and thresholding elements in chapter 5 — we are in principle able to build different simple neural network systems which would be able to perform associative tasks, feature extraction or solve nonlinear decision problems. However, for a large range of more complex networks as e.g. all multilayer networks using error backpropagation, it is convenient to have recursion to a number of computational functions that enable to detect and process differences between the desired and the actual output or that visualize temporal changes in the two-dimensional representation of the input.
KeywordsDiffraction Efficiency Saturable Absorber Ring Resonator Reference Beam Pump Wave
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