| 1. |
- Johansson, Eija, 1982, et al.
(author)
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Interpolation based on stationary and adaptive AR(1) modeling
- 2011
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 4052-4055
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Conference paper (peer-reviewed)abstract
- In this paper, we describe a minimal mean square error (MMSE) optimal interpolation filter for discrete random signals. We explicitly derive the interpolation filter for a first-order autoregressive process (AR(1)), and show that the filter depends only on the two adjacent points. The result is extended by developing an algorithm called local AR approximation (LARA), where a random signal is locally estimated as an AR(1) process. Experimental evaluation illustrates that LARA interpolation yields a lower mean square error than other common interpolation techniques, including linear, spline and local polynomial approximation (LPA).
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| 2. |
- Khan, Zulfiqar Hasan, 1976, et al.
(author)
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Adaptive appearance learning for visual object tracking
- 2011
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 1413-1416
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Conference paper (peer-reviewed)abstract
- This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspondences, and the mean shift under the Bayesian framework, respectively. The reference object distribution is built up by a kernel-weighted color histogram. The main contributions of the proposed schemes includes: (a) an adaptive learning strategy that seeks to update the reference object distribution when the changes are caused by the intrinsic object dynamic without partial occlusion/ intersection; (b) novel dynamic maintenance of object feature points by exploring both foreground and background sets; (c) integration of adaptive appearance and local point features in joint object appearance similarity and local point features correspondences-based tracker to improve [7]; (d) integration of adaptive appearance in jointappearance similarity and particle filter tracker under theBayesian framework to improve [10]. Experimental results on a range of videos captured by a dynamic/stationary camerademonstrate the effectiveness of the proposed schemes in terms of robustness to partial occlusions, tracking drifts and tightness and accuracy of tracked bounding box. Comparisons are also made with the two hybrid trackers together with 3 existing trackers.
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| 3. |
- Matthaiou, Michail, 1981, et al.
(author)
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On the sum rate of ZF detectors in correlated K fading MIMO channels
- 2011
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 3244-3247
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Conference paper (peer-reviewed)abstract
- This paper presents a detailed sum rate investigation of Zero-Forcing (ZF) detectors over composite multiple-input multiple-output (MIMO) channels. To this end, we consider the generic K distribution (Rayleigh/gamma distribution) to model the composite fading fluctuations and also assume the general case of semi-correlated small-scale fading. Novel exact analytical expressions are derived for the achievable sum rate followed by asymptotic expressions in the low Signal-to-Noise ratio (SNR) regime. In parallel, new, closed-form upper and lower bounds on the sum rate are derived that remain tight for all SNRs. The theoretical analysis is validated via a set of Monte-Carlo simulations.
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| 4. |
- Monir Vaghefi, Sayed Reza, 1985, et al.
(author)
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RSS-based sensor localization with unknown transmit power
- 2011
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 2480-2483
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Conference paper (peer-reviewed)abstract
- Received signal strength (RSS)-based single source localization when there is not a prior knowledge about the transmit power of the source is investigated. Because of nonconvex behavior of maximum likelihood (ML) estimator, convoluted computations are required to achieve its global minimum. Therefore, we propose a novel semidefinite programming (SDP) approach by approximating ML problem to a convex optimization problem which can be solved very efficiently. Computer simulations show that our proposed SDP has a remarkable performance very close to ML estimator. Linearizing RSS model, we also derive the partly novel least squares (LS) and weighted total least squares (WTLS) algorithms for this problem. Simulations illustrate that WTLS improves the performance of LS considerably.
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| 5. |
- Panahi, Ashkan, 1986, et al.
(author)
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Maximum a Posteriori Based Regularization Parameter Selection
- 2011
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781457705397 ; , s. 2452-2455
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Conference paper (peer-reviewed)abstract
- The l(1) norm regularized least square technique has been proposed as an efficient method to calculate sparse solutions. However, the choice of the regularization parameter is still an unsolved problem, especially when the number of nonzero elements is unknown. In this paper we first design different ML estimators by interpreting the l(1) norm regularization as a MAP estimator with a Laplacian model for data. We also utilize the MDL criterion to decide on the regularization parameter. The performance of these new methods are evaluated in the context of estimating the Directions Of Arrival (DOA) for the simulated data and compared. The simulations show that the performance of the different forms of the MAP estimator are approximately equal in the one snapshot case, where MDL may not work. But for the multiple snapshot case both methods can be used.
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| 6. |
- Savic, Vladimir, et al.
(author)
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Optimized edge appearance probability for cooperative localization based on tree-reweighted nonparametric belief propagation
- 2011
-
In: Proc. of IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP). - 1520-6149. - 9781457705380 - 9781457705397 ; , s. 3028-3031
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Conference paper (peer-reviewed)abstract
- Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible non-convergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRW-NBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.
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| 7. |
- Björnson, Emil, et al.
(author)
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Massive MIMO systems with hardware-constrained base stations
- 2014
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. - 9781479928927 ; , s. 3142-3146
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Conference paper (peer-reviewed)abstract
- Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas. Such large antenna arrays offer huge spatial degrees-of-freedom for transmission optimization; in particular, great signal gains, resilience to imperfect channel knowledge, and small inter-user interference are all achievable without extensive inter-cell coordination. The key to cost-efficient deployment of large arrays is the use of hardware-constrained base stations with low-cost antenna elements, as compared to today's expensive and power-hungry BSs. Low-cost transceivers are prone to hardware imperfections, but it has been conjectured that the excessive degrees-of-freedom of massive MIMO would bring robustness to such imperfections. We herein prove this claim for an uplink channel with multiplicative phase-drift, additive distortion noise, and noise amplification. Specifically, we derive a closed-form scaling law that shows how fast the imperfections increase with the number of antennas.
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| 8. |
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| 9. |
- Ahrens, Jens, 1978
(author)
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Auralization of Omnidirectional Room Impulse Responses Based on the Spatial Decomposition Method and Synthetic Spatial Data
- 2019
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. ; , s. 146-150
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Conference paper (peer-reviewed)abstract
- The spatial decomposition method decomposes acoustic room impulse responses into a pressure signal and a direction of arrival for each time instant of the pressure signal. An acoustic space can be auralized by distributing the pressure signal over the available loudspeakers or head-related transfer functions so that the required instantaneous propagation direction is recreated. We present a user study that demonstrates based on binaural auralization that the arrival directions can be synthesized from random data such that the auralization is nearly indistinguishable from the auralization of the original data. The presented concept constitutes the fundament of a highly scalable spatialization method for omnidirectional room impulse responses.
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| 10. |
- Ahrens, Jens, 1978, et al.
(author)
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Interpolation and Range Extrapolation of Sound Source Directivity Based on a Spherical Wave Propagation Model
- 2020
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In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. - 1520-6149. ; 2020-May, s. 4662-4666
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Conference paper (peer-reviewed)abstract
- Approaches for incorporating sound source directivity into wave-based room acoustic simulations using a spherical harmonic representation have been presented recently. Normally, the directivity is measured or prescribed on a spherical surface centered at the nominal source position. In wave-based simulations, this directivity can be represented through a locally-defined driving term acting at the source location. In practice, the directivity of real-world sound sources like musical instruments or industrial machinery can only be measured approximately in terms of spatial resolution and accuracy. We show that the measurement data can be augmented such that the impairments due to the limitations of the measurement accuracy are mitigated. We revisit the previously proposed approach of only using the angle-dependent magnitude of the measured directivity together with a spherical-wave propagation model and demonstrate its potential by means of numerical simulations based on two case studies.
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