Complex electron wave reconstruction using parameter estimation

The interpolation approaches to the shape recovery of a speech signal in transmission over packet switched communications nelworks are proposed. The samples of a signal fragments are mixed and transmitted in correspondence with standard procedure of packet-switched transmission. After reception a reverse permutation is made. In the case of packet losses missing samples are separated by several samples of the source signal. Correlation properties of the signal are used for the recovey samples due to the first-and second-order non-adaptive and adaptive interpolation. For the loss of 25% packets and second order adaptive interpolation are 2-4% error distribution range has been achieved.0-7803-5432-X/99/$10.00 0 1999 IEEE

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“…Interpolation of samples was applied in [6]. A signal is divided into two groups, the even and the odd samples.…”

Section: Basic Interpolation Principlementioning

confidence: 99%

Speech signal recovery in packet-switched communication networks

Zagursky

Ginters²

1999 IEEE AUTOTESTCON Proceedings (Cat. No.99CH36323)

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Digitized circular arcs: characterization and parameter estimation

Worring

Smeulders

1995

IEEE Trans. Pattern Anal. Machine Intell.

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Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety

Adalı

Schreier

Scharf

2011

IEEE Trans. Signal Process.

340

284

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Complex-valued signals occur in many areas of science and engineering and are thus of fundamental interest. In the past, it has often been assumed, usually implicitly, that complex random signals are proper or circular. A proper complex random variable is uncorrelated with its complex conjugate, and a circular complex random variable has a probability distribution that is invariant under rotation in the complex plane. While these assumptions are convenient because they simplify computations, there are many cases where proper and circular random signals are very poor models of the underlying physics. When taking impropriety and noncircularity into account, the right type of processing can provide significant performance gains. There are two key ingredients in the statistical signal processing of complexvalued data: (1) utilizing the complete statistical characterization of complex-valued random signals; and (2) the optimization of real-valued cost functions with respect to complex parameters. In this overview article, we review the necessary tools, among which are widely linear transformations, augmented statistical descriptions, and Wirtinger calculus. We also present some T.

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Complex electron wave reconstruction using parameter estimation

Cited by 3 publications

References 3 publications

Speech signal recovery in packet-switched communication networks

Speech signal recovery in packet-switched communication networks

Digitized circular arcs: characterization and parameter estimation

Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety

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