| 1. |
- Faundez-Zanuy, M., et al.
(författare)
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On the relevance of bandwidth extension for speaker identification
- 2015
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Ingår i: European Signal Processing Conference. - : EUSIPCO. - 2219-5491.
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we discuss the relevance of bandwidth extension for speaker identification tasks. Mainly we want to study if it is possible to recognize voices that have been bandwith extended. For this purpose, we created two different databases (microphonic and ISDN) of speech signals that were bandwidth extended from telephone bandwidth ([300, 3400] Hz) to full bandwidth ([100, 8000] Hz). We have evaluated different parameterizations, and we have found that the MELCEPST parameterization can take advantage of the bandwidth extension algorithms in several situations.
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| 2. |
- McKelvey, Tomas, 1966
(författare)
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Auto-calibration of Uniform Linear Array Antennas
- 2019
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Ingår i: European Signal Processing Conference. - 2219-5491. ; 2019-September
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Konferensbidrag (refereegranskat)abstract
- Calibration is instrumental to realize the full performance of a measurement system. In this contribution we consider the calibration of a uniformly linear array antenna where we assume each antenna element has an unknown complex gain. We present an algorithm which can be used to calibrate the array without full knowledge of the environment. Particularly, if the number of signal sources are known we show that we can determine the individual unknown antenna gains up to an ambiguity parametrized by a single complex scalar. If the ratio of the complex gains between two consecutive elements is also known, this ambiguity is resolved. The method is based on determining the antenna calibration parameters such that the Hankel matrix of the array snapshots has a given rank. A numerical example illustrates the performance of the method. The numerical results suggest that the method is consistent in SNR.
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| 3. |
- Olmos, Salvador, et al.
(författare)
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Subspace detectors for multichannel signals
- 2015
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Ingår i: European Signal Processing Conference. - 2219-5491. ; 2015-March
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Tidskriftsartikel (refereegranskat)abstract
- In this paper a multichannel subspace detector is proposed based on a separable spatio-temporal linear model. The generalized likelihood ratio test (GLRT) for this model is derived for the case of coloured Gaussian noise and known temporal and covariance matrices. Simulation results support the theory and illustrate the benefits of the spatio-temporal detector versus channel-by-channel detectors for low values of SNR.
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| 4. |
- Ozcelikkale, Ayca, 1982, et al.
(författare)
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Transmission Strategies for Remote Estimation under Energy Harvesting Constraints
- 2016
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Ingår i: European Signal Processing Conference. - 2219-5491. - 9780992862657 ; 2016-November, s. 572-576
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Konferensbidrag (refereegranskat)abstract
- We consider the remote estimation of a time- correlated field using an energy harvesting (EH) sensor. The sensor observes the unknown field and communicates its observa- tions to a remote fusion center using an amplify-forward strategy. We consider the design of optimal transmission strategies in order to minimize the mean-square error (MSE) at the fusion center. Contrary to traditional approaches, the degree of correlation between the field values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios, including the circularly wide-sense stationary (c.w.s.s.) signals with static correlation coefficient and the sampled low-pass c.w.s.s. signals. Based on these results, we propose low-complexity policies for the general case. Numerical evaluations illustrate the performance of the optimal and the low-complexity policies.
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| 5. |
- Veen, Alle Jan Van Der, et al.
(författare)
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Minimal continuous state-space parametrizations
- 2015
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Ingår i: European Signal Processing Conference. - 2219-5491.
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Konferensbidrag (refereegranskat)abstract
- We present a minimal continuous parametrization of all multivariate rational contractive transfer functions.In contrast to traditional minimal parametrizations, this parametrization does not contain any structural indices, which makes it very suitable for identification algorithms that use nonlinear optimization to estimate the parameters.
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| 6. |
- Vinge, Rikard, 1990, et al.
(författare)
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Understanding Support Vector Machines with Polynomial Kernels
- 2019
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Ingår i: European Signal Processing Conference. - 2219-5491. - 9789082797039 ; 2019-September
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Konferensbidrag (refereegranskat)abstract
- Interpreting models learned by a support vector machine (SVM) is often difficult, if not impossible, due to working in high-dimensional spaces. In this paper, we present an investigation into polynomial kernels for the SVM. We show that the models learned by these machines are constructed from terms related to the statistical moments of the support vectors. This allows us to deepen our understanding of the internal workings of these models and, for example, gauge the importance of combinations of features. We also discuss how the SVM with a quadratic kernel is related to the likelihood-ratio test for normally distributed populations.
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