Asymptotic performance of unrestricted polar quantizers
IEEE Transactions on Information Theory
An on-line variable-length binary encoding of text
Information Sciences: an International Journal
Optimal encoding of non-stationary sources
Information Sciences: an International Journal - Dictionary based compression
Digital Coding of Waveforms: Principles and Applications to Speech and Video
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Variable-length Codes for Data Compression
Variable-length Codes for Data Compression
Optimal companding vector quantization for circularly symmetric sources
Information Sciences: an International Journal
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IEEE Transactions on Audio, Speech, and Language Processing
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Information Sciences: an International Journal
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Information Sciences: an International Journal
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Information Sciences: an International Journal
Polar coordinate quantizers that minimize mean-squared error
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
Asymptotically efficient quantizing
IEEE Transactions on Information Theory
Quantization schemes for bivariate Gaussian random variables
IEEE Transactions on Information Theory
Two-dimensional quantization of bivariate circularly symmetric densities
IEEE Transactions on Information Theory
Multidimensional spherical coordinates quantization
IEEE Transactions on Information Theory
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This paper considers the application of variable-length coding using two unrestricted polar quantizers (UPQs) for performance improvement of unrestricted polar quantization for bivariate Gaussian source. We propose the use of two UPQs, both designed for the bivariate Gaussian source of unit variance, having different sizes of codebooks and different optimal compressor functions. We show that the fixed-rate UPQ is a subset of our model, and we perform rigorous optimization procedure in order to obtain optimal parameter values maximizing the signal to quantization noise ratio (SQNR) for the given average bit rate. In addition, we study how gain in SQNR over the fixed-rate UPQ depends on the average bit rate and we show that the gain ranges from 0.619dB to 0.869dB depending on the average bit rate. Discussion is also provided about the proposed quantizer complexity and its performance in comparison to Shannon limit. The proposed UPQ provides a sophisticated choice of average bit rate compared to the fixed-rate UPQ. Features of the proposed quantizer indicate that the obtained model should be of high theoretical and practical significance.