摘要：This paper proposes a simple manner to determine the support region of the quasilogarithmic robust quantizer. We assume Laplacian probability density function which is widely accepted as a good approximation to the actual distribution of audio and speech samples. Theoretically, the proposed model offers high performance in terms of adaptability and robustness, while the numerical results point out at the fact that the proposed approach to the observed support region threshold determination provides good results in a wide dynamic range from the standpoint of the signal to quantization noise ratio (SQNR). Additionally, we propose an iterative method for support region determination, which stops when further improvement in mean-squared error (MSE) becomes negligible. The ssuggested model is useful for compression schemes that involve trade-offs between quantizer design and implementation complexity.
其他摘要：This paper proposes a simple manner to determine the support region of the quasilogarithmic robust quantizer. We assume Laplacian probability density function which is widely accepted as a good approximation to the actual distribution of audio and speech samples. Theoretically, the proposed model offers high performance in terms of adaptability and robustness, while the numerical results point out at the fact that the proposed approach to the observed support region threshold determination provides good results in a wide dynamic range from the standpoint of the signal to quantization noise ratio (SQNR). Additionally, we propose an iterative method for support region determination, which stops when further improvement in mean-squared error (MSE) becomes negligible. The ssuggested model is useful for compression schemes that involve trade-offs between quantizer design and implementation complexity. DOI: http://dx.doi.org/10.5755/j01.itc.47.4.20668
关键词：quasilogarithmic quantizer;support region threshold;scaling coefficient
其他关键词：quasilogarithmic quantizer;support region threshold;scaling coefficient
