| 1. |
- Kronvall, Ted, et al.
(författare)
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Online Group-Sparse Regression Using the Covariance Fitting Criterion
- 2017
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Ingår i: Proceedings of the 25th European Signal Processing Conference (EUSIPCO). - 2076-1465. - 9780992862688 ; CFP1740S-USB
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present a time-recursive implementation of a recent hyperparameter-free group-sparse estimation technique. This is achieved byr eformulating the original method, termed group-SPICE, as a square-root group-LASSO with a suitable regularization level, for which a time-recursive implementation is derived. Using a proximal gradient step for lowering the computational cost, the proposed method may effectively cope with data sequences consisting of both stationary and non-stationary signals, such as transients, and/or amplitude modulated signals. Numerical examples illustrates the efficacy of the proposed method for both coherent Gaussian dictionaries and for the multi-pitch estimation problem.
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| 2. |
- Angelopoulos, Kostas, et al.
(författare)
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Efficient Time Recursive Coherence Spectrum Estimation
- 2012
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Ingår i: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2076-1465 .- 2219-5491. - 9781467310680 ; , s. 425-429
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Konferensbidrag (refereegranskat)abstract
- The coherence spectrum is of notable interest as a bivariate spectral measure in a variety of application, and the topic has lately attracted notable interest with the recent formulation of several high-resolution data adaptive estimators. In this work, we present computationally efficient time recursive implementations of the recent iterative adaptive approach (IAA) estimator, examining both the case of complete data sets and when some observations are missing. The algorithms continues the recent development of exploiting the estimators’ inherently low displacement rank of the necessary products of Toeplitz-like matrices, extending these to time-updating formulations for the IAA-based coherence estimation algorithm. Numerical simulations together with theoretical complexity measures illustrate the performance of the proposed algorithm.
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| 3. |
- Aström, Kalle, et al.
(författare)
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Extension of Time-Difference-of-Arrival Self Calibration Solutions Using Robust Multilateration
- 2021
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Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2076-1465 .- 2219-5491. - 9789082797060 ; , s. 870-874
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Konferensbidrag (refereegranskat)abstract
- Recent advances in robust self-calibration have made it possible to estimate microphone positions and at least partial sound source positions using ambient sound. However, there are limits on how well sound source paths can be recovered using state-of-the-art techniques. In this paper we develop and evaluate several techniques to extend partial and incomplete solutions. We present minimal solvers for sound source positioning using non-overlapping pairs of microphone positions and their respective time-difference measurements, and show how these new solvers can be used in a hypothesis and test setting. We also investigate techniques that exploit temporal smoothness of the sound source paths. The different techniques are evaluated on both real and synthetic data, and compared to several state-of-the-art techniques for time-difference-of-arrival multilateration.
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| 4. |
- Björnson, Emil, et al.
(författare)
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DISTRIBUTED MASSIVE MIMO IN CELLULAR NETWORKS: IMPACT OF IMPERFECT HARDWARE AND NUMBER OF OSCILLATORS
- 2015
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Ingår i: 2015 23rd European Signal Processing Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 2076-1465. - 9780992862633 ; , s. 2436-2440
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Konferensbidrag (refereegranskat)abstract
- Distributed massive multiple-input multiple-output (MIMO) combines the array gain of coherent MIMO processing with the proximity gains of distributed antenna setups. In this paper, we analyze how transceiver hardware impairments affect the downlink with maximum ratio transmission. We derive closed-form spectral efficiencies expressions and study their asymptotic behavior as the number of the antennas increases. We prove a scaling law on the hardware quality, which reveals that massive MIMO is resilient to additive distortions, while multiplicative phase noise is a limiting factor. It is also better to have separate oscillators at each antenna than one per BS.
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| 5. |
- Elvander, Filip, et al.
(författare)
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Robust Non-Negative Least Squares Using Sparsity
- 2016
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Ingår i: 2016 24th European Signal Processing Conference (EUSIPCO). - 2076-1465. - 9780992862657 ; , s. 61-65
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Konferensbidrag (refereegranskat)abstract
- Sparse, non-negative signals occur in many applications. To recover such signals, estimation posed as non-negative least squares problems have proven to be fruitful. Efficient algorithms with high accuracy have been proposed, but many of them assume either perfect knowledge of the dictionary generating the signal, or attempts to explain deviations from this dictionary by attributing them to components that for some reason is missing from the dictionary. In this work, we propose a robust non-negative least squares algorithm that allows the generating dictionary to differ from the assumed dictionary, introducing uncertainty in the setup. The proposed algorithm enables an improved modeling of the measurements, and may be efficiently implemented using a proposed ADMM implementation. Numerical examples illustrate the improved performance as compared to the standard non-negative LASSO estimator.
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| 6. |
- Jensen, Jesper, et al.
(författare)
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Computationally Efficient IAA-Based Estimation of the Fundamental Frequency
- 2012
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Ingår i: Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European. - 2076-1465 .- 2219-5491. - 9781467310680 ; , s. 2163-2167
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Konferensbidrag (refereegranskat)abstract
- Optimal linearly constrained minimum variance (LCMV) filtering methods have recently been applied to fundamental frequency estimation. Like many other fundamental frequency estimators, these methods are constructed using an estimate of the inverse data covariance matrix. The required matrix inverse is typically formed using the sample covariance matrix via data partitioning, although this is well-known to adversely affect the spectral resolution. In this paper, we propose a fast implementation of a novel optimal filtering method that utilizes the LCMV principle in conjunction with the iterative adaptive approach (IAA). The IAA formulation enables an accurate covariance matrix estimate from a single snapshot, i.e., without data partitioning, but the improvement comes at a notable computational cost. Exploiting the estimator's inherently low displacement rank of the necessary products of Toeplitz-like matrices, we form a computationally efficient implementation, reducing the required computational complexity with several orders of magnitude. The experimental results show that the performance of the proposed method is comparable or better than that of other competing methods in terms of spectral resolution.
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| 7. |
- Kronvall, Ted, et al.
(författare)
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An Adaptive Penalty Approach to Multi-Pitch Estimation
- 2015
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Ingår i: Signal Processing Conference (EUSIPCO), 2015 23rd European. - 2076-1465. - 9780992862633
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Konferensbidrag (refereegranskat)abstract
- This work treats multi-pitch estimation, and in particular the common misclassification issue wherein the pitch at half of the true fundamental frequency, here referred to as a sub-octave, is chosen instead of the true pitch. Extending on current methods which use an extension of the Group LASSO for pitch estimation, this work introduces an adaptive total variation penalty, which both enforce group- and block sparsity, and deal with errors due to sub-octaves. The method is shown to outperform current state-of-the-art sparse methods, where the model orders are unknown, while also requiring fewer tuning parameters than these. The method is also shown to outperform several conventional pitch estimation methods, even when these are virtued with oracle model orders.
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| 8. |
- Kronvall, Ted, et al.
(författare)
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Multi-pitch estimation via fast group sparse learning
- 2016
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Ingår i: 2016 24th European Signal Processing Conference (EUSIPCO). - 2076-1465. - 9780992862657 ; , s. 1093-1097
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Konferensbidrag (refereegranskat)abstract
- In this work, we consider the problem of multi-pitch estimation using sparse heuristics and convex modeling. In general, this is a difficult non-linear optimization problem, as the frequencies belonging to one pitch often overlap the frequencies belonging to other pitches, thereby causing ambiguity between pitches with similar frequency content. The problem is further complicated by the fact that the number of pitches is typically not known. In this work, we propose a sparse modeling framework using a generalized chroma representation in order to remove redundancy and lower the dictionary's block-coherency. The found chroma estimates are then used to solve a small convex problem, whereby spectral smoothness is enforced, resulting in the corresponding pitch estimates. Compared with previously published sparse approaches, the resulting algorithm reduces the computational complexity of each iteration, as well as speeding up the overall convergence.
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| 9. |
- Nagano-Madsen, Yasuko, 1952, et al.
(författare)
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Perception and Production of L2 Mandarin Tones by Swedish Learners
- 2017
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Ingår i: 2017 25th European Signal Processing Conference (EUSIPCO). - : Institute of Electrical and Electronics Engineers (IEEE). - 9780992862671 ; , s. 578-582
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Konferensbidrag (refereegranskat)abstract
- This study presents the results of perception and production of L2 Mandarin tones in mono- and di-syllabic words by Swedish learners at the beginner level. Although studies of perception and production on Mandarin tones are many, those by speakers of lexical-pitch accent language such as Swedish are still very limited. The result reveals both discrepancy and agreement between perception and production. Swedish learners perform best in discriminating a level tone (T1) from contour tones (T2, T3, T4) both in perception and production. Discrepancy between perception and production was noted for T3. In perception, the identification of T3 was second best after the level tone (T1), but the production of T3 was found to be difficult.
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| 10. |
- Ribeiro, Eduardo, et al.
(författare)
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Exploring Deep Learning Image Super-Resolution for Iris Recognition
- 2017
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Ingår i: 25th European Signal Processing Conference (EUSIPCO 2017). - : Institute of Electrical and Electronics Engineers (IEEE). - 9780992862671 - 9780992862688 - 9781538607510 ; , s. 2176-2180
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Konferensbidrag (refereegranskat)abstract
- In this work we test the ability of deep learning methods to provide an end-to-end mapping between low and high resolution images applying it to the iris recognition problem. Here, we propose the use of two deep learning single-image super-resolution approaches: Stacked Auto-Encoders (SAE) and Convolutional Neural Networks (CNN) with the most possible lightweight structure to achieve fast speed, preserve local information and reduce artifacts at the same time. We validate the methods with a database of 1.872 near-infrared iris images with quality assessment and recognition experiments showing the superiority of deep learning approaches over the compared algorithms. © EURASIP 2017.
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