Least squares quantization in PCM
Квантование методом наименьших квадратов в PCM
1982-03-01
SCID: 54.1/9xcy2w6x
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Gaussian and Laplacian signal amplitude distributionsaverage quantization noise power minimizationleast squares quantizationoptimum finite quantization schemespulse-code modulation (PCM)
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Abstract (AI)
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.
Key Findings
1
Derived necessary conditions that optimum finite PCM quantization levels and their intervals must satisfy to minimize average quantization noise power.
2
Provided numerical optimal quantization schemes for 2^b quanta (b = 1..7) for Gaussian signal amplitude distributions.
3
Provided numerical optimal quantization schemes for 2^b quanta (b = 1..7) for Laplacian signal amplitude distributions.
4
Showed that the finite-quantum result reduces to Panter and Dite’s asymptotic one-third-power law as the number of quanta becomes large.
Research Object
Finite pulse-code modulation (PCM) quantization scheme (quanta and associated quantization intervals) for a given signal amplitude ensemble
Research Subject
Necessary conditions and optimization (minimization of average quantization noise power) for placement of quanta and interval boundaries in finite PCM, including numerical optimal schemes for 2^{b} quanta and their asymptotic relation to the one-third power law
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1982-03-01
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