Alcatel-Lucent

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.

New insights into the noise reduction Wiener filter

Abstract: The problem of noise reduction has attracted a considerable amount of research attention over the past several decades. Among the numerous techniques that were developed, the optimal Wiener filter can be considered as one of the most fundamental noise reduction approaches, which has been delineated in different forms and adopted in various applications. Although it is not a secret that the Wiener filter may cause some detrimental effects to the speech signal (appreciable or even significant degradation in quality or intelligibility), few efforts have been reported to show the inherent relationship between noise reduction and speech distortion. By defining a speech-distortion index to measure the degree to which the speech signal is deformed and two noise-reduction factors to quantify the amount of noise being attenuated, this paper studies the quantitative performance behavior of the Wiener filter in the context of noise reduction. We show that in the single-channel case the a posteriori signal-to-noise ratio (SNR) (defined after the Wiener filter) is greater than or equal to the a priori SNR (defined before the Wiener filter), indicating that the Wiener filter is always able to achieve noise reduction. However, the amount of noise reduction is in general proportional to the amount of speech degradation. This may seem discouraging as we always expect an algorithm to have maximal noise reduction without much speech distortion. Fortunately, we show that speech distortion can be better managed in three different ways. If we have some a priori knowledge (such as the linear prediction coefficients) of the clean speech signal, this a priori knowledge can be exploited to achieve noise reduction while maintaining a low level of speech distortion. When no a priori knowledge is available, we can still achieve a better control of noise reduction and speech distortion by properly manipulating the Wiener filter, resulting in a suboptimal Wiener filter. In case that we have multiple microphone sensors, the multiple observations of the speech signal can be used to reduce noise with less or even no speech distortion

Making the future safe for the past: adding genericity to the Java programming language

Abstract: We present GJ, a design that extends the Java programming language with generic types and methods. These are both explained and implemented by translation into the unextended language. The translation closely mimics the way generics are emulated by programmers: it erases all type parameters, maps type variables to their bounds, and inserts casts where needed. Some subtleties of the translation are caused by the handling of overriding.GJ increases expressiveness and safety: code utilizing generic libraries is no longer buried under a plethora of casts, and the corresponding casts inserted by the translation are guaranteed to not fail.GJ is designed to be fully backwards compatible with the current Java language, which simplifies the transition from non-generic to generic programming. In particular, one can retrofit existing library classes with generic interfaces without changing their code.An implementation of GJ has been written in GJ, and is freely available on the web.

On approximating arbitrary metrices by tree metrics

Abstract: We design a generation algorithm for a problem which a&es in computational chemistry: the random generation of models of amorphous strutures. Such structures can be modeled as graphs which see embedded in d-space. The algorithm uses the well known approach of simulating a rapidly-mixing Markov chain. Gur analysis of the Mixing rate is based on Dobrushin uniqueness. The structure of the problem forces us to extend the basic method and find an alternative to Dobrushin’s condition which is more appropriate for our problem. This extension appears to be of more general interest.

Measurement of the Force-Velocity Relation for Growing Microtubules

Abstract: Forces generated by protein polymerization are important for various forms of cellular motility. Assembling microtubules, for instance, are believed to exert pushing forces on chromosomes during mitosis. The force that a single microtubule can generate was measured by attaching microtubules to a substrate at one end and causing them to push against a microfabricated rigid barrier at the other end. The subsequent buckling of the microtubules was analyzed to determine both the force on each microtubule end and the growth velocity. The growth velocity decreased from 1.2 micrometers per minute at zero force to 0.2 micrometer per minute at forces of 3 to 4 piconewtons. The force-velocity relation fits well to a decaying exponential, in agreement with theoretical models, but the rate of decay is faster than predicted.

Exploiting hardware performance counters with flow and context sensitive profiling

Abstract: A program profile attributes run-time costs to portions of a program's execution. Most profiling systems suffer from two major deficiencies: first, they only apportion simple metrics, such as execution frequency or elapsed time to static, syntactic units, such as procedures or statements; second, they aggressively reduce the volume of information collected and reported, although aggregation can hide striking differences in program behavior.This paper addresses both concerns by exploiting the hardware counters available in most modern processors and by incorporating two concepts from data flow analysis--flow and context sensitivity--to report more context for measurements. This paper extends our previous work on efficient path profiling to flow sensitive profiling, which associates hardware performance metrics with a path through a procedure. In addition, it describes a data structure, the calling context tree, that efficiently captures calling contexts for procedure-level measurements.Our measurements show that the SPEC95 benchmarks execute a small number (3--28) of hot paths that account for 9--98% of their L1 data cache misses. Moreover, these hot paths are concentrated in a few routines, which have complex dynamic behavior.