9,631 research outputs found

    Characterization of SINR Region for Multiple Interfering Multicast in Power-Controlled Systems

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    This paper considers a wireless communication network consisting of multiple interfering multicast sessions. Different from a unicast system where each transmitter has only one receiver, in a multicast system, each transmitter has multiple receivers. It is a well known result for wireless unicast systems that the feasibility of an signal-to-interference-plus-noise power ratio (SINR) without power constraint is decided by the Perron-Frobenius eigenvalue of a nonnegative matrix. We generalize this result and propose necessary and sufficient conditions for the feasibility of an SINR in a wireless multicast system with and without power constraint. The feasible SINR region as well as its geometric properties are studied. Besides, an iterative algorithm is proposed which can efficiently check the feasibility condition and compute the boundary points of the feasible SINR region.Comment: 25 pages, 4 figures, submitted to IEEE Trans. Inform. Theor

    On the Rapid Spin-down and Low Luminosity Pulsed Emission from AE Aquarii

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    AE Aqr is an unusual close binary system with a very short white dwarf spin period, a high spin-down rate, a relatively low quiescent luminosity, and clear pulse signals. The exact nature of the large spin-down power has not been well explained mainly due to the fact that the observed luminosities in various energy ranges are much lower than the spin-down power. We consider an unconventional picture of AE Aqr in which an accreting white dwarf, modeled as a magnetic dipole whose axis is misaligned with the spin axis, is rapidly spun-down via gravitational radiation emission and therefore the spin-down power is not directly connected to any observable electromagnetic emission.Comment: 25 pages and one PS figure, Submitted to Ap

    The effects of the carrier interaction and electric fields on subband structures of selectively--doped semiconductor quantum wells

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    We investigate the ground--state electronic properties of the symmetrically-- doped semiconductor quantum well in the presence of a homogeneous electric field. In this paper we examined the effect of the electric field and carrier interaction on the subband structure as a function of the field strength and carrier concentration. The many--body effects are evaluated using a local density functional exchange--correlation potential. We find that the electron subband energy is reduced as the magnitude of the electric field is increased, but it is increased as the surface carrier density is increased. However, the separation of the electron subband energies is reduced for the increase in both the electric field and surface carrier density. On the other hand, the energy separation of the hole subbands is increased as the carrier density and field strength are increased. Effect of the exchange--correlation potential on the subband structure is found negligibly small in this calculation. The subband energies are reduced slightly, increasing their separations little in the presence of the local exchange--correlation potential.Comment: 17 pages, revtex, 11 figures(available on request

    Forecasting the detectability of known radial velocity planets with the upcoming CHEOPS mission

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    The Characterizing Exoplanets Satellite (CHEOPS) mission is planned for launch next year with a major objective being to search for transits of known RV planets, particularly those orbiting bright stars. Since the radial velocity method is only sensitive to planetary mass, the radii, transit depths and transit signal-to-noise values of each RV planet are, a-priori, unknown. Using an empirically calibrated probabilistic mass-radius relation, forecaster (Chen & Kipping 2017a), we address this by predicting a catalog of homogeneous credible intervals for these three keys terms for 468 planets discovered via radial velocities. Of these, we find that the vast majority should be detectable with CHEOPS, including terrestrial bodies, if they have the correct geometric alignment. In particular, we predict that 22 mini-Neptunes and 82 Neptune-sized planets would be suitable for detection and that more than 80% of these will have apparent magnitude of V < 10, making them highly suitable for follow-up characterization work. Our work aims to assist the CHEOPS team in scheduling efforts and highlights the great value of quantifiable, statistically robust estimates for upcoming exoplanetary missions.Comment: Accepted to MNRAS, results available at https://github.com/CoolWorlds/cheopsforecast

    Improved Audio Embeddings by Adjacency-Based Clustering with Applications in Spoken Term Detection

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    Embedding audio signal segments into vectors with fixed dimensionality is attractive because all following processing will be easier and more efficient, for example modeling, classifying or indexing. Audio Word2Vec previously proposed was shown to be able to represent audio segments for spoken words as such vectors carrying information about the phonetic structures of the signal segments. However, each linguistic unit (word, syllable, phoneme in text form) corresponds to unlimited number of audio segments with vector representations inevitably spread over the embedding space, which causes some confusion. It is therefore desired to better cluster the audio embeddings such that those corresponding to the same linguistic unit can be more compactly distributed. In this paper, inspired by Siamese networks, we propose some approaches to achieve the above goal. This includes identifying positive and negative pairs from unlabeled data for Siamese style training, disentangling acoustic factors such as speaker characteristics from the audio embedding, handling unbalanced data distribution, and having the embedding processes learn from the adjacency relationships among data points. All these can be done in an unsupervised way. Improved performance was obtained in preliminary experiments on the LibriSpeech data set, including clustering characteristics analysis and applications of spoken term detection

    From Semi-supervised to Almost-unsupervised Speech Recognition with Very-low Resource by Jointly Learning Phonetic Structures from Audio and Text Embeddings

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    Producing a large amount of annotated speech data for training ASR systems remains difficult for more than 95% of languages all over the world which are low-resourced. However, we note human babies start to learn the language by the sounds (or phonetic structures) of a small number of exemplar words, and "generalize" such knowledge to other words without hearing a large amount of data. We initiate some preliminary work in this direction. Audio Word2Vec is used to learn the phonetic structures from spoken words (signal segments), while another autoencoder is used to learn the phonetic structures from text words. The relationships among the above two can be learned jointly, or separately after the above two are well trained. This relationship can be used in speech recognition with very low resource. In the initial experiments on the TIMIT dataset, only 2.1 hours of speech data (in which 2500 spoken words were annotated and the rest unlabeled) gave a word error rate of 44.6%, and this number can be reduced to 34.2% if 4.1 hr of speech data (in which 20000 spoken words were annotated) were given. These results are not satisfactory, but a good starting point

    Towards Unsupervised Automatic Speech Recognition Trained by Unaligned Speech and Text only

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    Automatic speech recognition (ASR) has been widely researched with supervised approaches, while many low-resourced languages lack audio-text aligned data, and supervised methods cannot be applied on them. In this work, we propose a framework to achieve unsupervised ASR on a read English speech dataset, where audio and text are unaligned. In the first stage, each word-level audio segment in the utterances is represented by a vector representation extracted by a sequence-of-sequence autoencoder, in which phonetic information and speaker information are disentangled. Secondly, semantic embeddings of audio segments are trained from the vector representations using a skip-gram model. Last but not the least, an unsupervised method is utilized to transform semantic embeddings of audio segments to text embedding space, and finally the transformed embeddings are mapped to words. With the above framework, we are towards unsupervised ASR trained by unaligned text and speech only.Comment: Code is released: https://github.com/grtzsohalf/Towards-Unsupervised-AS

    Information-Theoretic Caching: Sequential Coding for Computing

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    Under the paradigm of caching, partial data is delivered before the actual requests of users are known. In this paper, this problem is modeled as a canonical distributed source coding problem with side information, where the side information represents the users' requests. For the single-user case, a single-letter characterization of the optimal rate region is established, and for several important special cases, closed-form solutions are given, including the scenario of uniformly distributed user requests. In this case, it is shown that the optimal caching strategy is closely related to total correlation and Wyner's common information. Using the insight gained from the single-user case, three two-user scenarios admitting single-letter characterization are considered, which draw connections to existing source coding problems in the literature: the Gray--Wyner system and distributed successive refinement. Finally, the model studied by Maddah-Ali and Niesen is rephrased to make a comparison with the considered information-theoretic model. Although the two caching models have a similar behavior for the single-user case, it is shown through a two-user example that the two caching models behave differently in general.Comment: submitted to IEEE Trans. Inf. Theory and presented in part at ISIT 201

    Estimating Supermassive Black Hole Mass Through Radio/X-Ray Luminosity Relation of X-Ray Bright Galactic Nuclei

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    It has been suggested that optically thin and geometrically thick accretion flows are responsible for the observed radio/X-ray luminosity relation of the X-ray bright galactic nuclei. If this is the case then central supermassive black hole masses can be estimated directly from measurements of the core radio luminosity and the X-ray luminosity, provided that properties of such accretion flows are known. Calculated ratios of the luminosities are presented in cases of the standard ADAF model and modified ADAF models, in which a truncation of inner parts of the flows and winds causing a reduction of the infalling matter are included. We compare the observed ratio of the luminosities with predictions from models of optically thin accretion flows. We also discuss the possible effects of the convection in ADAFs. We confirm that the supermassive black hole (SMBH) mass estimate is possible with the radio/X-ray luminosity relation due to ADAF models in the absence of a radio jet. We find that observational data are insufficient to distinguish the standard ADAF model from its modified models. However, the ADAF model with convection is inconsistent with observations, unless microphysics parameters are to be substantially changed. High resolution radio observations are required to avoid the contamination of other components, such as, a jet component. Otherwise, the SMBH mass is inclined to be over-estimated.Comment: 19 pages, 3 ps figures, Submitted to ApJ

    Observations of Spectral and Time Variabilities from MCG-2-58-22

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    We present results from analysis of the X-ray archive data of MCG-2-58-22, acquired with ROSAT from 1991 to 1993 and with ASCA from 1993 to 1997. By analyzing light curves, we find that MCG-2-58-22 shows a clear time variability in X-ray flux. The time scales of the variations range widely from about 1000 s to more than years. Among the variations, a flare-like event overlaid on the gradual flux decrease from 1979 to 1993 is detected. We also find clear time variability of the spectra in the energy range of 0.1 - 2.0 keV. However, the flux variation does not influences on their spectra in the energy range of 2 - 10 keV. The implications of these observational results are discussed in terms of a supermassive black hole model and accretion flow dynamics near the central black hole.Comment: 27 pages and 9 figures, submitted to Ap
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