Spectrum | EPFL Graph Search

A spectrum (: spectra or spectrums) is a condition that is not limited to a specific set of values but can vary, without gaps, across a continuum. The word was first used scientifically in optics to describe the rainbow of colors in visible light after passing through a prism. As scientific understanding of light advanced, it came to apply to the entire electromagnetic spectrum. It thereby became a mapping of a range of magnitudes (wavelengths) to a range of qualities, which are the perceived "colors of the rainbow" and other properties which correspond to wavelengths that lie outside of the visible light spectrum. Spectrum has since been applied by analogy to topics outside optics. Thus, one might talk about the "spectrum of political opinion", or the "spectrum of activity" of a drug, or the "autism spectrum". In these uses, values within a spectrum may not be associated with precisely quantifiable numbers or definitions. Such uses imply a broad range of conditions or behaviors gro

High Performance InP-Based Quantum Dash Semiconductor Mode-Locked Lasers for Optical Communications

Anthony Martinez

Several applications are pushing the development of high performance mode-locked lasers: generation of short pulses for extremely high bit rate transmission at 100 Gb/s and beyond, all-optical clock recovery at 40 Gb/s and beyond, generation of millimeter wave signals through mode-beating on a high speed photodiode, optical sampling for analog-to-digital conversion, and generation of wavelength-division-multiplexing channels. This paper will report on new advances in InP-based quantum dash mode-locked lasers, which largely surpass the performance of their bulk or quantum well counterparts in terms of the mode-beating spectral purity and the bandwidth of optical spectrum. In particular, we will describe the quantum dash nanostructures used for the mode-locked lasers and the dependence of the mode-locking properties on detailed quantum dash structures. We will demonstrate that these quantum dash lasers can be actively mode-locked, generating sub-picosecond or picosecond pulses at different repetition frequencies with extremely low timing jitter. They can also be used to achieve all-optical clock recovery, with timing jitter compliant with International Telecommunication Union (ITU) standards even for highly degraded input optical signal-to-noise ratio. Finally, we demonstrate that, owing to the very wide and flat optical spectrum and the low relative-intensity noise level of the mode-locked laser, error-free transmission over 50 km single mode fiber has been achieved for eight wavelength division multiplexing ITU channels at 10 Gb/s with a channel spacing of 100 GHz. (C) 2009 Alcatel-Lucent.

2009

Semi-supervised Extraction of Audio-Visual Sources

Patricia Calatayud Martinez

This report presents a semi-supervised method to jointly extract audio-visual sources from a scene. It consist of applying a supervised method to segment the video signal followed by an automatic process to properly separate the audio track. This approach starts with the user interaction to select the audio-visual target we want to cut. This labels the problem into two parts. One is the foreground, the object we aim to extract. The background is the remaining content which sets the other part. The segmentation method will be performed over the video signal to split its visual content into foreground and background. It is based on describing the video information as a volume. It is composed of pixels and relationships among them which set the features of the problem. This 3D structure can be interpreted as a graph. Therefore the segmentation is achieved by applying a Graph Cuts algorithm which provides the suitable results. In this work the audio separation process is an automatic task. Due to this we need to extract prior information from the audio-visual data available. Therefore a link between audio and video channels is deﬁned by an audio-visual motion map. This is a video sequence which provides the amount of synchronous motion with the audio track. An audio-based video diﬀusion method have been developed to obtain this kind of signal. Applying the video segmentation labelling to the audio-visual motion map we obtain the distribution of the amount motion into foreground and background. According to the range of these values it is possible to asses when the corresponding audio is on/oﬀ. At this point, audio samples of sources can be extract when the audio activity is due to only one. This is the prior information to learn audio models by means of spectral GMM estimation to assess the audio signals. Finally the separation method is applied. It consist of looking for the more suitable couple of states given the mixture spectrum of the total audio track. Therefore we achieve the audio separation goal. In this work we will study in detail all the stages towards the ﬁnal aim of our method, analyzing the performances of our approach.

2010

Semi-supervised Extraction of Audio-Visual Sources

Patricia Calatayud Martinez

2010