Reduced Complexity LSF Vector Quantization with Switched-Adaptive Prediction (CROSBI ID 491051)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Petrinović, Davorka ; Petrinović, Davor
engleski
Reduced Complexity LSF Vector Quantization with Switched-Adaptive Prediction
A modification of a classical Predictive Vector Quantization (PVQ) technique with switched-adaptive prediction for line spectrum frequencies (LSF) quantization is proposed in this paper, enabling significant reduction in complexity. Lower complexity is achieved through use of higher number of switched prediction matrices but with reduced number of their non-zero elements. The structures of such matrices and optimal matrix elements are obtained to maximize the quantizer closed-loop prediction gain. A comparison of the proposed quantizer to the ones with full prediction matrices as well as to the quantizer incorporating diagonal matrices is given. The effectiveness of the proposed approach is shown and the trade-off between complexity and quality of the quantizer is analyzed.
vector linear prediction; sparse matrices; complexity reduction; LSF quantization
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Podaci o prilogu
Vol II, 1039-104-x.
2003.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis (ISPA 2003)
S.Lončarić, A. Neri, H. Babić
Rim: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu
Podaci o skupu
International Symposium on Image and Signal Processing and Analysis, ISPA'03
poster
18.09.2003-20.09.2003
Rim, Italija