| 1. |
- Bergman, Svante, 1979-, et al.
(författare)
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Lattice based linear precoding for MIMO block codes
- 2007
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Ingår i: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. - : IEEE. - 1424407281 - 1424407273 ; , s. 329-332
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Konferensbidrag (refereegranskat)abstract
- Herein, the design of linear dispersion codes for block based multiple-input multiple-output communication systems is investigated. The receiver as well as the transmitter are assumed to have perfect knowledge of the channel, and the receiver is assumed to employ maximum likelihood detection. We propose to use linear precoding and lattice invariant operations to transform the channel matrix into a lattice with large coding gain. With appropriate approximations, it is shown that this corresponds to selecting lattices with good sphere packing properties. Lattice invariant transformations are then used to minimize the power consumption. An algorithm for this power minimization is presented along with a lower bound on the optimization. Numerical results indicate that there is a potential gain of several dB by using the method compared to channel inversion with adaptive bit loading.
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| 2. |
- Brun, Anders, 1976-, et al.
(författare)
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Intrinsic and Extrinsic Means on the Circle -- a Maximum Likelihood Interpretation
- 2007
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Ingår i: ICASSP 2007. IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. - New York, USA : IEEE. - 1424407273 ; , s. III-1053-III-1056
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Konferensbidrag (refereegranskat)abstract
- For data samples in Rn, the mean is a well known estimator. When the data set belongs to an embedded manifold M in Rn, e.g. the unit circle in R2, the definition of a mean can be extended and constrained to M by choosing either the intrinsic Riemannian metric of the manifold or the extrinsic metric of the embedding space. A common view has been that extrinsic means are approximate solutions to the intrinsic mean problem. This paper study both means on the unit circle and reveal how they are related to the ML estimate of independent samples generated from a Brownian distribution. The conclusion is that on the circle, intrinsic and extrinsic means are maximum likelihood estimators in the limits of high SNR and low SNR respectively
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| 3. |
- Garrido, Mario, 1981-, et al.
(författare)
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Efficient Memoryless Cordic for FFT Computation
- 2007
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Ingår i: Efficient Memoryless Cordic for FFT Computation. - : IEEE. - 1424407281 - 1424407273 ; , s. II-113-II-116
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Konferensbidrag (refereegranskat)abstract
- A new memoryless CORDIC algorithm for the FFT computation is proposed in this paper. This approach calculates the direction of the micro-rotations from the control counter of the FFT, so the area of the rotator hardly depends on the number of rotations, which is particularly suitable for the computation of FFTs of a high number of points. Moreover, the new CORDIC presents other advantages such as the simplification of the basic CORDIC processor used to calculate the micro-rotations, or an easy way to compensate the intrinsic gain of the CORDIC algorithm. Additionally, the VLSI implementation of the algorithm is a pipeline architecture with high performance in terms of speed, throughput and latency.
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| 4. |
- Mowlér, Marc, et al.
(författare)
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Methods and bounds for antenna array coupling matrix estimation
- 2007
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Ingår i: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. - : IEEE. - 1424407273 - 1424407281 ; , s. 881-884
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Konferensbidrag (refereegranskat)abstract
- A novel method is proposed for estimation of the mutual coupling matrix of an antenna array. The method extends previous work by incorporating an unknown phase center and the element factor (antenna radiation pattern) in the model, and treating these as nuisance parameters during the estimation of coupling. To facilitate this, a parametrization of the element factor based on a truncated Fourier series is proposed. The Cramer-Rao bound (CRB) for the estimation problem is derived and used to analyze how the required amount of measurement data increases when introducing a more and more flexible model for the element factor. Finally, the performance of the proposed estimator is illustrated using data from measurements on an 8-element antenna array.
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| 5. |
- Parraga, Adriane, et al.
(författare)
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Quality Assessment of Non-rigid Registration Methods for Atlas-based Segmentation in Head-neck Radiotherapy
- 2007
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Ingår i: ICASSP 2007. - : IEEE. - 1424407273 ; , s. I-445-I-448
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Konferensbidrag (refereegranskat)abstract
- In this paper we compare three non-rigid registration methods for atlas-based segmentation: B-splines, morphons and a combination of morphons and demons. To assess the quality of each method, we use a data set of four patients, containing for each patient the computed tomography (CT) image and a manual segmentation of the organs at risk performed by an expert of the head and neck anatomy. Non-rigid registration algorithms have been used to match the patient and atlas images. Each deformation field, resulting from the non-rigid deformation, have been applied on the masks corresponding to segmented regions in the atlas. The atlas based segmented masks have been compared to manual segmentations performed by the expert. The results show that the combined method (morphons + demons) achieves the best performances on this dataset resulting in an average improvement of 6% with respect to morphons and 18% with respect to B-spline.
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| 6. |
- Persson, Daniel, et al.
(författare)
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A Minimum Mean Square Error Estimation and Mixture-Based Approach to Packet Video Error Concealment
- 2007
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Ingår i: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. - 1424407273 ; , s. 749-752
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Konferensbidrag (refereegranskat)abstract
- In this paper, a minimum mean square error-optimized mixture-based estimator is used for packet video error concealment. At the same time as on-line computational complexity is reduced, performance in peak signal-to-noise ratio (PSNR) is increased in comparison with a Gaussian mixture-based estimator that obtains its parameters through probability density estimation by means of the expectation maximization algorithm. Moreover, our method increases performance in PSNR compared to several other previous error concealment algorithms
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| 7. |
- Selén, Yngve, et al.
(författare)
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Empirical bayes linear regression with unknown model order
- 2007
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Ingår i: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol III, Pts 1-3, Proceedings. - : IEEE. - 1424407281 - 9781424407286 - 1424407273 ; , s. 773-776
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Konferensbidrag (refereegranskat)abstract
- We study the maximum a posteriori probability model order selection algorithm for linear regression models, assuming Gaussian distributed noise and coefficient vectors. For the same data model, we also derive the minimum mean-square error coefficient vector estimate. The approaches are denoted BOSS (Bayesian Order Selection Strategy) and BPM (Bayesian Parameter estimation Method), respectively. Both BOSS and BPM require a priori knowledge on the distribution of the coefficients. However, under the assumption that the coefficient variance profile is smooth, we derive "empirical Bayesian" versions of our algorithms, which require little or no information from the user. We show in numerical examples that the estimators can outperform several classical methods, including the well-known AIC and BIC for order selection.
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| 8. |
- Skoglund, Mikael, et al.
(författare)
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Optimal modulation for known interference
- 2007
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Ingår i: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. - : IEEE. - 1424407281 - 1424407273 ; , s. 233-236
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Konferensbidrag (refereegranskat)abstract
- We present a symbol-by- symbol approach to the problem of canceling known interference at the transmitter in a communication system. In the envisioned system, the modulator maps an information symbol (taken from a finite alphabet) and an interference symbol (from the complex field) onto a transmitted constellation point. The demodulator picks the information symbol (as a function of the received symbol) which minimizes the average error probability. We find the optimal modulator-demodulator pair, in the minimum-probability-of-symbol-error sense, via an iterative optimization procedure, for fixed average transmit power. We illustrate that the new scheme can perform close to the no-interference bound, and in particular that it outperforms Tomlinson-Harashima precoding, which is a classical but suboptimal solution to the problem under study.
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| 9. |
- Statovci, D., et al.
(författare)
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Dynamic Spectrum Management for Standardized VDSL
- 2007
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Ingår i: IEEE International Conference on Acoustics, Speech and Signal Processing. - Piscataway, N.J. : IEEE Press. - 1424407273 ; , s. III-73
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Konferensbidrag (refereegranskat)abstract
- Dynamic spectrum management (DSM) improves the capacity utilization of twisted-pair cables by adapting the transmit power spectral density (PSD) of modems to the actual noise environment and channel conditions. Earlier proposed DSM algorithms do not take into account the standardized very high speed digital subscriber line (VDSL) constraints on the allowable transmit PSDs. However, VDSL modems support only restricted transmit PSD shapes resulting from the standardized power back-off (PBO) method, which is controlled by a small set of parameters. Furthermore, since all modems are currently using the same PBO parameters their bit rate performance is severely limited. In this paper, we show how to effectively exploit the standardized PBO concept for DSM to significantly boost bit rates. We also present a low complex DSM algorithm, the user unique PBO (UUPBO) algorithm, for calculating PBO parameters that are uniquely optimized for each modem. © 2007 IEEE.
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| 10. |
- Tsontzos, Georgios, et al.
(författare)
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Estimation of general identifiable linear dynamic models with an application in speech recognition
- 2007
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Ingår i: 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol IV, Pts 1-3. - 1424407273 ; , s. 453-456
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Konferensbidrag (refereegranskat)abstract
- Although Hidden Markov Models (HMMs) provide a relatively efficient modeling framework for speech recognition, they suffer from several shortcomings which set upper bounds in the performance that can be achieved. Alternatively, linear dynamic models (LDM) can be used to model speech segments. Several implementations of LDM have been proposed in the literature. However, all had a restricted structure to satisfy identifiability constraints. In this paper, we relax all these constraints and use a general, canonical form for a linear state-space system that guarantees identifiability for arbitrary state and observation vector dimensions. For this system,we present a novel, element-wise Maximum Likelihood (ML) estimation method. Classification experiments on the AURORA2 speech database show performance gains compared to HMMs, particularly on highly noisy conditions.
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