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Design of trellis coded vector quantizers using Kohonen maps

✍ Scribed by Chi-Sing Leung; Lai-Wan Chan

Book ID
104348975
Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
534 KB
Volume
12
Category
Article
ISSN
0893-6080

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✦ Synopsis

Although the performance of trellis coded vector quantizers (TCVQs) is much better than that of conventional memoryless vector quantizers, designing the trellis in TCVQs has a certain amount of computational overhead. In this paper, we apply Kohonen maps to simplify the design process of the TCVQs by exploiting the ordering property of Kohonen maps. This new implementation of the TCVQs is named as trellis coded Kohonen maps (TCKMs). Simulation results show that, with such a simple design process, the performance of the TCKMs is still comparable to that of the conventional TCVQs.

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## Abstract Kohonen's model as the self‐organizing model for the neural network can be considered as a kind of adaptive vector quantization algorithm. Numerous reports have been presented on the application of the model to practical problems. Although some results have been presented for the theore