Abstract
Delta Modulation (DM) is a simple waveform coding algorithm used mostly when timely data delivery is more important than the transmitted data quality. While the implementation of DM is fairly simple and inexpensive, it suffers from several limitations, such as slope overload and granular noise, which can be overcome using Adaptive Delta Modulation (ADM). This paper presents novel 2-digit ADM with six-level quantization using variable-length coding, for encoding the time-varying signals modelled by Laplacian distribution. Two variants of quantizer are employed, distortion-constrained quantizer which is optimally designed for minimal mean-squared error (MSE), and rate-constrained quantizer, which is suboptimal in the minimal MSE sense, but enables minimal loss in SQNR for the target bit rate. Experimental results using real speech signal are provided, indicating that the proposed configuration outperforms the baseline ADM algorithms, including Constant Factor Delta Modulation (CFDM), Continuously Variable Slope Delta Modulation (CVSDM), 2-digit and 2-bit ADM, and operates in a much wider dynamic range.
| Original language | English |
|---|---|
| Pages (from-to) | 1085-1100 |
| Number of pages | 16 |
| Journal | International Journal of Electronics |
| Volume | 106 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 3 Jul 2019 |
| Externally published | Yes |
Keywords
- Delta modulation
- Laplacian source
- SNR
- predictive coding
- speech coding
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