基于广义Hebbian算法的图像压缩技术

2017 4th International Conference on Signal Processing, Computing and Control (ISPCC) Pub Date : 2017-09-01 DOI:10.1109/ISPCC.2017.8269750

Sagar Sachdeva, Vinay Kumar, V. Bawa

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引用次数: 0

摘要

在这篇手稿中，神经网络架构被用于图像压缩。我们利用神经网络结构分析了主成分分析技术，其中突触权重作为主成分，通过广义Hebbian算法(GHA)进行训练。通过与传统PCA的比较，演示和说明了GHA在图像压缩方面的训练和能力。

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Generalized Hebbian Algorithm based technique for image compression

In this manuscript neural networks architecture is used for image compression. We analyzed the PCA technique with the help of neural networks architecture in which the synaptic weights act as the principal components which are trained through the Generalized Hebbian Algorithm (GHA). A comparison with traditional PCA is performed to demonstrate and illustrate the training and capabilities of the GHA for image compression.

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2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)

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