신경회로망을 이용한 신호 자동식별기 구현 및 성능분석

On the Performance Analysis of an Automatic Neural Network Signal Classifier

  • 발행 : 1994.11.18

초록

In this paper a feature-based automatic neural network signal classifier is presented, where five neural network algorithms such as MLP, RBF, LVQ2, MLP-Tree and LVQ-Tree are combined in parallel to classifiy various signals from their features, based on the majority vote method. To demonstrate the performance and applicability of the proposed signal classifier, some test results for the classification of synthetic waveforms and power disturbances are provided.

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