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A simple and complete asymptotical analysis of an optimal piecewise uniform quantization of two-dimensional memoryless Laplacian source with the respect to distortion (D) i.e. the mean-square error (MSE) is presented. Piecewise uniform quantization consist ...
The transceivers of a wireless sensor network (WSN) have to fulfill the low-power and low-voltage constraints. The WiseNET project has already proven that it is possible to design a receiver working at 1V and consuming less than 2mW. However this transceiv ...
This paper studies quantization error in the context of Matching Pursuit coded streams and proposes a new coefficient quantization scheme taking benefit of the Matching Pursuit properties. The coefficients energy in Matching Pursuit indeed decreases with t ...
This paper addresses the problem of optimal rate allocation for multiple description coding with redundant signal expansions. In case of redundant descriptions, the quantization of the transform coefficients has clearly to be adapted to the importance of t ...
Motivated by biological neural networks and distributed sensing networks, we study how pooling networks – or quantizers – with random thresholds can be used in detection tasks. We provide a brief overview of the use of deterministic quantizers in detection ...
In this paper, we describe additional experiments based on a novel audio coding technique that uses an autoregressive model to approximate an audio signal's Hilbert envelope. This technique is performed over long segments (1000 ms) in critical-band-sized s ...
This paper addresses the problem of optimal rate allocation for multiple description coding with redundant signal expansions. In case of redundant descriptions, the quantization of the transform coefficients has clearly to be adapted to the importance of t ...
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The modelling of natural gas combustion with detailed as well as reduced kinetic mechanisms has been subject to many publications already. Most of the mechanisms are validated at higher temperatures and ambient pressures. Only recently - in parallel to a g ...
Building good sparse approximations of functions is one of the major themes in approximation theory. When applied to signals, images or any kind of data, it allows to deal with basic building blocks that essentially synthesize all the information at hand. ...
This paper addresses the problem of optimal rate allocation for multiple description coding with redundant signal expansions. In case of redundant descriptions, the quantization of the transform coefficients has clearly to be adapted to the importance of t ...