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Journal ArticleDOI

Embedded DPCM for Variable Bit Rate Transmission

David J. Goodman
- 01 Jul 1980 - 
- Vol. 28, Iss: 7, pp 1040-1046
TLDR
In this paper, an adaptive DPCM (ADPCM) encoder and decoder is proposed for variable rate transmission with variable bit rates up to any desired maximum. But the decoded analog signal is substantially noisier than the output of an ADPCM encoder with D = E - C bits/sample.
Abstract
Within the bit stream of an embedded digital code is a stream that can be decoded to produce a reasonable replica of the analog source signal. Unlike pulse code modulation (PCM), differential PCM (DPCM), is not an embedded code. If C bits/sample are delected from the bit stream of a DPCM encoder with E bits/sample, the decoded analog signal is substantially noisier than the output of a DPCM codec with D = E - C bits/sample. The penalty is 4-10 dB in signal-to-noise ratio (snr). However, with minor modifications to the encoder and decoder, DPCM becomes an embedded code. Embedded DPCM with E bits/ sample at the encoder and D bits/sample transmitted produces exactly the same output as embedded DPCM with D bits/sample encoding and perfect transmission. The snr of embedded DPCM is slightly lower than the Snr of DPCM. The penalty is 0.5-0.8 dB if the minimum transmitted bit rate is 2 bits/sample. It is less than 0.3 dB if D is at least 3 bits/sample. Combined with an appropriate adaptive quantizer the embedded DPCM codec produces embedded ADPCM (adaptive DPCM) for variable rate transmission ranging from 2 bits/sample up to any desired maximum. Applications exist in speech interpolation, packet switching, and hardware architecture.

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Citations
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Effects of Packet Losses in Waveform Coded Speech and Improvements Due to an Odd-Even Sample-Interpolation Procedure

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Patent

Multiple access cellular communication with dynamic slot allocation and reduced co-channel interference

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References
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Book

Digital Processing of Speech Signals

TL;DR: This paper presents a meta-modelling framework for digital Speech Processing for Man-Machine Communication by Voice that automates the very labor-intensive and therefore time-heavy and expensive process of encoding and decoding speech.
Journal ArticleDOI

Adaptive quantization with a one-word memory

TL;DR: By including an adequate range of values for N and Δ START in a generalized SNR definition, it is shown how one can determine stable multiplier functions M OPT that are optimal for a given signal.
Journal ArticleDOI

Theory of an Adaptive Quantizer

TL;DR: A bound is obtained for the tradeoff between responsiveness to changing input level and steady-state range accuracy.
Journal ArticleDOI

A Robust Adaptive Quantizer

TL;DR: A related quantizer is introduced which has the advantage of disipating the effects of transmission errors at any desired rate and is applied to the modification of a quantizer currently used for speech.
Journal ArticleDOI

Comparative Discussion of Circuit- vs. Packet-Switched Voice

TL;DR: This paper explores the robustness of comparisons for a range of network architectures and demonstrates that network sizing as related to the number of voice channels traversing a particular transmission link, and network topology with respect to theNumber of tandem links utilized in an end-to-end connection can have significant effects on the system performance.
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