Frequency adaptive learning SOFM for grayscale image compression

Frequency adaptive learning SOFM for grayscale image compression

A new learning algorithm is proposed where the learning constant is based on the localized winning frequency of each individual neuron. Blocks of sub-image are fed in a butterfly-jumping sequence during the training process. Untrained neurons are also re-initialized.

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Bibliographic Details
Main Author: Tan, Chiang Poo.
Other Authors: Chang, Chip Hong
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:http://hdl.handle.net/10356/3336
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Institution: Nanyang Technological University
Description
Summary:A new learning algorithm is proposed where the learning constant is based on the localized winning frequency of each individual neuron. Blocks of sub-image are fed in a butterfly-jumping sequence during the training process. Untrained neurons are also re-initialized.

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