%0 Journal Article %1 1056489 %A Lloyd, S. %D 1982 %J Information Theory, IEEE Transactions on %K AWM2012 TopicClustering algorithm kmeans %N 2 %P 129-137 %T Least squares quantization in PCM %V 28 %X It has long been realized that in pulse-code modulation (PCM), with a given ensemble of signals to handle, the quantum values should be spaced more closely in the voltage regions where the signal amplitude is more likely to fall. It has been shown by Panter and Dite that, in the limit as the number of quanta becomes infinite, the asymptotic fractional density of quanta per unit voltage should vary as the one-third power of the probability density per unit voltage of signal amplitudes. In this paper the corresponding result for any finite number of quanta is derived; that is, necessary conditions are found that the quanta and associated quantization intervals of an optimum finite quantization scheme must satisfy. The optimization criterion used is that the average quantization noise power be a minimum. It is shown that the result obtained here goes over into the Panter and Dite result as the number of quanta become large. The optimum quautization schemes for2^bquanta,b=1,2, cdots, 7, are given numerically for Gaussian and for Laplacian distribution of signal amplitudes.

@article{1056489, abstract = { It has long been realized that in pulse-code modulation (PCM), with a given ensemble of signals to handle, the quantum values should be spaced more closely in the voltage regions where the signal amplitude is more likely to fall. It has been shown by Panter and Dite that, in the limit as the number of quanta becomes infinite, the asymptotic fractional density of quanta per unit voltage should vary as the one-third power of the probability density per unit voltage of signal amplitudes. In this paper the corresponding result for any finite number of quanta is derived; that is, necessary conditions are found that the quanta and associated quantization intervals of an optimum finite quantization scheme must satisfy. The optimization criterion used is that the average quantization noise power be a minimum. It is shown that the result obtained here goes over into the Panter and Dite result as the number of quanta become large. The optimum quautization schemes for2^{b}quanta,b=1,2, cdots, 7, are given numerically for Gaussian and for Laplacian distribution of signal amplitudes.}, added-at = {2012-05-07T17:33:45.000+0200}, author = {Lloyd, S.}, biburl = {https://www.bibsonomy.org/bibtex/2fac85566dea21d02ddbb6d70dcaec06b/archduke}, interhash = {aed766ae6b3f698a660ff38126308180}, intrahash = {fac85566dea21d02ddbb6d70dcaec06b}, issn = {0018-9448}, journal = {Information Theory, IEEE Transactions on}, keywords = {AWM2012 TopicClustering algorithm kmeans}, month = mar, number = 2, pages = { 129-137}, timestamp = {2012-05-07T17:33:45.000+0200}, title = {Least squares quantization in PCM}, volume = 28, year = 1982 }