DocumentCode
1086468
Title
On the power spectrum of the staircase function in linear delta modulation
Author
Jayant, Nuggehally S.
Author_Institution
Bell Laboratories, Murray Hill, NJ
Volume
23
Issue
2
fYear
1975
fDate
4/1/1975 12:00:00 AM
Firstpage
162
Lastpage
168
Abstract
We consider the power spectrum Y(f) of the staircase sequence
in the linear delta modulation (LDM) of a band-limited signal sequence,
. Within the signal band Y(f) approximates the input spectrum X(f) with an accuracy that depends on two parameters: the LDM step-size Δ and the over-sampling F (ratio of sampling rate in LDM to the Nyquist rate for the bandlimited input), or equivalently, the correlation C between adjacent input samples. We demonstrate Y(f) dependencies on Δ and F (or C) using Gauss-Markov and speech inputs in a computer simulation. For speech, we consider the specific problem of preserving, in Y(J), the formant frequencies of a short-term input spectrum X(f). We observe, for example, when F = 9, that input resonances are shifted by amounts not exceeding perceptual limens, in an average sense, if Δ is within an estimated ± 6 dB of a step-size ΔOPT (which minimizes the mean-square-quantization error in the delta modulation of
). The fact that yr is a summation of r binary quantities makes the computation of Y(f) much simpler than that of X(f), in general; specifically Y(f) can be computed without any multiply operations. Therefore, in problems where the power spectrum is the desired end result (for example, in the visual monitoring of formant frequencies in speech) Y(f) can provide a useful and simply computed approximation to the input spectrum. With such special applications in mind, we consider the problem of implementing a Y(f) analyzer, and note two specific analyzer configurations.
in the linear delta modulation (LDM) of a band-limited signal sequence,
. Within the signal band Y(f) approximates the input spectrum X(f) with an accuracy that depends on two parameters: the LDM step-size Δ and the over-sampling F (ratio of sampling rate in LDM to the Nyquist rate for the bandlimited input), or equivalently, the correlation C between adjacent input samples. We demonstrate Y(f) dependencies on Δ and F (or C) using Gauss-Markov and speech inputs in a computer simulation. For speech, we consider the specific problem of preserving, in Y(J), the formant frequencies of a short-term input spectrum X(f). We observe, for example, when F = 9, that input resonances are shifted by amounts not exceeding perceptual limens, in an average sense, if Δ is within an estimated ± 6 dB of a step-size Δ
). The fact that yKeywords
Computer simulation; Delta modulation; Frequency; Gaussian processes; Helium; Monitoring; Quantization; Resonance; Sampling methods; Speech;
fLanguage
English
Journal_Title
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
0096-3518
Type
jour
DOI
10.1109/TASSP.1975.1162665
Filename
1162665
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