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Optimum quantizer performance for a class of non-Gaussian memoryless sources

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2 Author(s)

The performance of optimum quantizers subject to an entropy constraint is studied for a wide class of memoryless sources. For a general distortion criterion, necessary conditions are developed for optimality and a recursive algorithm is described for obtaining the optimum quantizer. Under a mean-square error criterion, the performance of entropy encoded uniform quantization of memoryless Gaussian sources is well-known to be within 0.255 bits/sample of the rate-distortion bound at relatively high rates. Despite claims to the contrary, it is demonstrated that similar performance can be expected for a wide range of memoryless sources. Indeed, for the cases considered, the worst case performance is observed to be less than 0.3 bits/sample from the rate-distortion bound, and in most cases this disparity is less at Iow rates.

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Information Theory, IEEE Transactions on  (Volume:30 ,  Issue: 3 )