R. Zamir and T. Berger, "Multiterminal source coding with high resolution," IEEE Trans. Inform. Theory, vol. 45, no. 1, pp. 106--117, Jan. 1999. Home/Search Document Details and Download
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Sequential Signal Encoding from Noisy Measurements.. - Papadopoulos.. (2001) (Correct)
....observations, in the context of low complexity encoding methods that are based on an additive control input. adding a control input prior to quantization is often used in applications involving lossy compression such as video and audio coding where it is commonly referred to as dithering [32] [33]. In some (but not all) of the cases we consider, the control input plays a role very similar to dithering. In this paper, we focus on the static case of the estimation problem depicted in Fig. 2 in which , i.e. we examine the problem of estimating a noise corrupted unknown parameter via ....
.... conversion in particular, it is noteworthy that, besides the interesting connections between the feedback schemes to successive approximation A D converters, all the control input encoding techniques we have considered have similarities to nonsubtractive and subtractive dithering techniques [32] [33], 38] 43] 44] For instance, in both the known control input case and the feedback case, knowledge of the control input is exploited by the estimator and compensated after quantization, although, unlike subtractive dithering, the control input is not simply subtracted off the quantized ....
R. Zamir and T. Berger, "Multiterminal source coding with high resolution, " IEEE Trans. Inform. Theory, vol. 45, pp. 106--117, 1999.
Joint Entropy-Constrained Multiterminal Quantization - Cardinal, Van Assche (2002) (Correct)
....by X and Y , and both corresponding distortions must be minimized. This problem is a rate distortion generalization of the Slepian Wolf (SW) distributed coding problem [1] and has to be distinguished from that of estimating a single source given two noisy observations X and Y of it. Following [2], we will refer to this latter problem as remote coding and to our problem as direct coding. We further assume that the quantization step is followed by an ideal SW entropy coder (# X , # Y , # 1 ) as illustrated on Fig. 1. This assumption does make sense since recent works such as [3] propose ....
....on Fig. 1. This assumption does make sense since recent works such as [3] propose practical coders operating close to the SW bounds. We propose to design a quantizer pair jointly minimizing the two distortions with constraints on the two bitrates predicted by the SW theorem. Zamir and Berger [2] show that at the high resolution limit there is no rate loss compared to the joint encoding of the two sources and that the optimal high resolution performance can be achieved by the composition of blind separate quantizers with a SW coder. They suggest the use of lattice quantizers for the ....
R. Zamir and T. Berger, "Multiterminal source coding with high resolution," IEEE Trans. Inform. Theory, vol. 45, no. 1, pp. 106--117, Jan. 1999.
On the Whiteness of High Resolution Quantization Errors - Viswanathan, Zamir (2000) Self-citation (Zamir) (Correct)
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R. Zamir and T. Berger. Multiterminal source coding with high resolution. IEEE Trans. Information Theory, IT-45:106--117.
Joint Entropy-Constrained Multiterminal Quantization - Cardinal, Van Assche (2002) (Correct)
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R. Zamir and T. Berger, "Multiterminal source coding with high resolution," IEEE Trans. Inform. Theory, vol. 45, no. 1, pp. 106--117, Jan. 1999.
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