To achieve a better trade-off between the vector dimension and the memory requirements of a vector quantizer (VQ),\nan entropy-constrained VQ (ECVQ) scheme with finite memory, called finite-state ECVQ (FS-ECVQ), is presented in this\npaper. The scheme consists of a finite-state VQ (FSVQ) and multiple component ECVQs. By utilizing the FSVQ, the\ninter-frame dependencies within source sequence can be effectively exploited and no side information needs to be\ntransmitted. By employing the ECVQs, the total memory requirements of the FS-ECVQ can be efficiently decreased\nwhile the coding performance is improved. An FS-ECVQ, designed for the modified discrete cosine transform (MDCT)\ncoefficients coding, was implemented and evaluated based on the Unified Speech and Audio Coding (USAC) scheme.\nResults showed that the FS-ECVQ achieved a reduction of the total memory requirements by about 11.3%, compared\nwith the encoder in USAC final version (FINAL), while maintaining a similar coding performance.
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