Jaringan neural Untuk Pengenalan Pola yang Invarian Terhadap Translasi Dan Rotan

Analog coupled neurons (CN) can be used in trainable pattern recognition systems. A training algorithm called Coupled Neuron Rule (CNR) is used to implement classification functions. A character recognition.system involving an invariance network and a trainable classifier is proposed. The invariance...

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Bibliographic Details
Main Author: Perpustakaan UGM, i-lib
Format: Article
Published: [Yogyakarta] : Universitas Gadjah Mada 1996
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Summary:Analog coupled neurons (CN) can be used in trainable pattern recognition systems. A training algorithm called Coupled Neuron Rule (CNR) is used to implement classification functions. A character recognition.system involving an invariance network and a trainable classifier is proposed. The invariance net can be trained to produce a set of outputs that are insensitive to translation and rotation of the retinal input patterns. The outputs of the invariance net are scrambled. When these outputs are fed to a trainable classifier, the final outputs are descrambled and the original patterns are reproduced in standard position and orientation