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Institution

Alcatel-Lucent

Stuttgart, Germany
About: Alcatel-Lucent is a based out in Stuttgart, Germany. It is known for research contribution in the topics: Signal & Network packet. The organization has 37003 authors who have published 53332 publications receiving 1430547 citations. The organization is also known as: Alcatel-Lucent S.A. & Alcatel.


Papers
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Journal ArticleDOI
28 Apr 2000-Science
TL;DR: The carrier-envelope phase of the pulses emitted by a femtosecond mode-locked laser is stabilized by using the powerful tools of frequency-domain laser stabilization to perform absolute optical frequency measurements that were directly referenced to a stable microwave clock.
Abstract: We stabilized the carrier-envelope phase of the pulses emitted by a femtosecond mode-locked laser by using the powerful tools of frequency-domain laser stabilization. We confirmed control of the pulse-to-pulse carrier-envelope phase using temporal cross correlation. This phase stabilization locks the absolute frequencies emitted by the laser, which we used to perform absolute optical frequency measurements that were directly referenced to a stable microwave clock.

2,499 citations

Journal ArticleDOI
TL;DR: In this article, the authors demonstrate experimentally that air-silica microstructure optical fibers can exhibit anomalous dispersion at visible wavelengths, and exploit this feature to generate an optical continuum 550 THz in width, extending from the violet to the infrared.
Abstract: We demonstrate experimentally for what is to our knowledge the first time that air–silica microstructure optical fibers can exhibit anomalous dispersion at visible wavelengths. We exploit this feature to generate an optical continuum 550 THz in width, extending from the violet to the infrared, by propagating pulses of 100-fs duration and kilowatt peak powers through a microstructure fiber near the zero-dispersion wavelength.

2,372 citations

Book ChapterDOI
TL;DR: In this paper, a self-contained derivation from basic principles such as the Euclidean algorithm, with a focus on applying it to wavelet filtering, is presented, which asymptotically reduces the computational complexity of the transform by a factor two.
Abstract: This article is essentially tutorial in nature. We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed into a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures. This decomposition corresponds to a factorization of the polyphase matrix of the wavelet or subband filters into elementary matrices. That such a factorization is possible is well-known to algebraists (and expressed by the formulaSL(n;R[z, z−1])=E(n;R[z, z−1])); it is also used in linear systems theory in the electrical engineering community. We present here a self-contained derivation, building the decomposition from basic principles such as the Euclidean algorithm, with a focus on applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the biorthogonal, i.e., non-unitary case. Like the lattice factorization, the decomposition presented here asymptotically reduces the computational complexity of the transform by a factor two. It has other applications, such as the possibility of defining a wavelet-like transform that maps integers to integers.

2,357 citations

Journal ArticleDOI
12 Jun 2005
TL;DR: DART is a new tool for automatically testing software that combines three main techniques, automated extraction of the interface of a program with its external environment using static source-code parsing, and dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths.
Abstract: We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static source-code parsing; (2) automatic generation of a test driver for this interface that performs random testing to simulate the most general environment the program can operate in; and (3) dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths. Together, these three techniques constitute Directed Automated Random Testing, or DART for short. The main strength of DART is thus that testing can be performed completely automatically on any program that compiles -- there is no need to write any test driver or harness code. During testing, DART detects standard errors such as program crashes, assertion violations, and non-termination. Preliminary experiments to unit test several examples of C programs are very encouraging.

2,346 citations

Journal ArticleDOI
TL;DR: This work provides a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs and shows that excellent performance at very high data rates can be attained with either.
Abstract: Recent advancements in iterative processing of channel codes and the development of turbo codes have allowed the communications industry to achieve near-capacity on a single-antenna Gaussian or fading channel with low complexity. We show how these iterative techniques can also be used to achieve near-capacity on a multiple-antenna system where the receiver knows the channel. Combining iterative processing with multiple-antenna channels is particularly challenging because the channel capacities can be a factor of ten or more higher than their single-antenna counterparts. Using a "list" version of the sphere decoder, we provide a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs. We exemplify our technique by directly transmitting symbols that are coded with a channel code; we show that iterative processing with even this simple scheme can achieve near-capacity. We consider both simple convolutional and powerful turbo channel codes and show that excellent performance at very high data rates can be attained with either. We compare our simulation results with Shannon capacity limits for ergodic multiple-antenna channel.

2,291 citations


Authors

Showing all 37011 results

NameH-indexPapersCitations
George M. Whitesides2401739269833
Yoshua Bengio2021033420313
John A. Rogers1771341127390
Zhenan Bao169865106571
Thomas S. Huang1461299101564
Federico Capasso134118976957
Robert S. Brown130124365822
Christos Faloutsos12778977746
Robert J. Cava125104271819
Ramamoorthy Ramesh12264967418
Yann LeCun121369171211
Kamil Ugurbil12053659053
Don Towsley11988356671
Steven P. DenBaars118136660343
Robert E. Tarjan11440067305
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202212
202130
202050
201983
2018215