NDLI: Reduced complexity LSF vector quantization with switched-adaptive prediction

Content Provider	IEEE Xplore Digital Library
Author	Petrinovic, D. Petrinovic, D.
Copyright Year	2003
Description	Author affiliation: Fac. of Electr. Eng. & Comput., Zagreb Univ., Croatia (Petrinovic, D.; Petrinovic, D.)
Abstract	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 nonzero 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.
Sponsorship	EURASIP - European Association for Signal Processing IEEE Signal Processing Soc
Starting Page	1039
Ending Page	1044
File Size	360733
Page Count	6
File Format	PDF
ISBN	953184061X
DOI	10.1109/ISPA.2003.1296444
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-09-18
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Sparse matrices Frequency Covariance matrix Speech coding Linear predictive coding Bit rate Computational complexity Image reconstruction Signal processing
Content Type	Text
Resource Type	Article

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