|Title:||Kolmogorov complexity of spherical vector quantizers||Journal:||9th Symposium on Neural Network Applications in Electrical Engineering, NEUREL 2008 Proceedings||First page:||47||Last page:||52||Conference:||9th Symposium on Neural Network Applications in Electrical Engineering, NEUREL 2008; Belgrade; Serbia; 25 September 2008 through 27 September 2008||Issue Date:||1-Dec-2008||ISBN:||978-142442904-2||DOI:||10.1109/NEUREL.2008.4685558||Abstract:||
In this paper, we investigate memory complexity of spherical vector quantizer from Kolmogorov's perspective. The method for expressing the quantizer as binary string is proposed and minimal description length of the string is considered as Kolmogorov complexity of the quantizer. The Kolmogorov complexity is compared to memory requirements of two main algorithms for spherical vector quantizer design: uniform spherical quantizer and generalized Lloyd-Max's algorithm. It is proven that first of them has the minimal memory requirements needed for spherical quantizer realization, while the other upper bounds the theoretical minimal description length of the quantizer.
|Keywords:||Kolmogorov complexity | Spherical quantizer | Turing machine | Vector quantizer||Publisher:||IEEE|
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