A Two−Stage Network for Radar Pattern Classification
Mohammad Ahmadian and Russell Pimmel find it convenient to use a multistage neural network
configuration, a two−stage network in particular, for classifying patterns. The patterns they study are
geometrical features of simulated radar targets.
Feature extraction is done in the first stage, while classification is done in the second. Moreover, the first stage
is made up of several networks, each for extracting a different estimable feature. Backpropagation is used for
learning in the first stage. They use a single network in the second stage. The effect of noise is also studied.
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C++ Neural Networks and Fuzzy Logic:Preface
A Classifier
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