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I present a method for lossy transform coding of digital audio that uses the Weyl symbol calculus for constructing the encoding and decoding transformation. The method establishes a direct connection between a time-frequency representation of the signal dependent threshold of masked noise and the encode/decode pair. The formalism also offers a time-frequency measure of perceptual entropy.
We review a class of methods that can be collected under the name nonlinear transform coding (NTC), which over the past few years have become competitive with the best linear transform codecs for images, and have superseded them in terms of rate--dis
We consider the phase retrieval problem, in which the observer wishes to recover a $n$-dimensional real or complex signal $mathbf{X}^star$ from the (possibly noisy) observation of $|mathbf{Phi} mathbf{X}^star|$, in which $mathbf{Phi}$ is a matrix of
We consider communication over a noisy network under randomized linear network coding. Possible error mechanism include node- or link- failures, Byzantine behavior of nodes, or an over-estimate of the network min-cut. Building on the work of Koetter
Compared with automatic speech recognition (ASR), the human auditory system is more adept at handling noise-adverse situations, including environmental noise and channel distortion. To mimic this adeptness, auditory models have been widely incorporat
While Shannons mutual information has widespread applications in many disciplines, for practical applications it is often difficult to calculate its value accurately for high-dimensional variables because of the curse of dimensionality. This paper is