Vector quantization and signal compression
Vector quantization and signal compression
Speech Coding Algorithms: Foundation and Evolution of Standardized Coders
Speech Coding Algorithms: Foundation and Evolution of Standardized Coders
On the support of MSE-optimal, fixed-rate, scalar quantizers
IEEE Transactions on Information Theory
Adaptive scalar quantization without side information
IEEE Transactions on Image Processing
Nonlinear speech coding model based on genetic programming
Applied Soft Computing
The general design of asymptotic unrestricted polar quantizers with square cells
Digital Signal Processing
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This paper proposes a novel waveform coding algorithm based on the forward adaptive technique with the goal to provide the overreaching of the signal to quantization noise ratio achievable by the coding solution designed according to G.711 standard. The novel algorithm performs frame-by-frame analysis of the input signal, according to which one of the two compandors, the restricted or the unrestricted one, is selected for the particular frame procession. The basic concept of the proposed algorithm is to enable a more preferable selection of the restricted compandor than the unrestricted one, since, in such a manner, an increase of the signal to quantization noise ratio can be provided. Since both the theoretical and the simulation results, which are obtained for the assumed input speech signal, indicate the performance improvement over the G.711 standard along with approximately 1 bit/sample compression, one can expect that the proposed algorithm will be effective in coding of signals, that as well as speech signals follow Laplacian distribution and have the time varying characteristics.