Asymptotic Optimality of Modified Spherical Codes with Scalar Quantization of Gain for Memoryless Gaussian Sources (Special Section on Information Theory and Its Applications)

概要

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This paper characterizes a class of optimal fixed-to-fixed length data compression codes for memoryless Gaussian sources that achieve asymptotically the rate-distortion bound under squared-error criterion. Any source output of blocklength n is encoded by two steps, i.e., 1) to quantize in gain by scholar quantizers and 2) to quantize in shape by pointsets on n-dimensional hyperspheres. To show the asymptotic optimality of the proposed codes, rate-distortion properties of the codes are analyzed in detail by using a random coding argument on the n-dimensional unit hypersphere. It is shown that asymptotic behaviors of the proposed codes are mainly determined by the choice of scalar quantizer of the gain. As a results, deep insights into not only the class of asymptotically optimal codes but also the rate-distortion bound itself are obtained.
社団法人電子情報通信学会の論文
1993-09-25