Abstract
This paper presents a forward mean-adaptive quasilogarithmic quantizer for correlated sources. This quantizer exploits the correlation between adjacent input signal samples, while keeping the low computational complexity. Quasilogarithmic quantizer is highly applicable, due to its robustness, providing approximately constant objective output signal quality, when applied to signals with different statistical characteristics. The impact of the application of various compression factors is also analyzed and described. The results obtained indicate that the forward mean-adaptive quasilogarithmic quantizer is suitable for the application in coding of highly correlated sources, as high quality speech and music signals.
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