| 1. |
- Ambat, Sooraj K., et al.
(författare)
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Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing
- 2014
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 97, s. 146-151
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Tidskriftsartikel (refereegranskat)abstract
- Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data.
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| 2. |
- Angelopoulos, Kostas, et al.
(författare)
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Computationally Efficient Sparsity-Inducing Coherence Spectrum Estimation of Complete and Non-Complete Data Sets
- 2013
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 93:5, s. 1221-1234
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Tidskriftsartikel (refereegranskat)abstract
- The magnitude squared coherence (MSC) spectrum is an often used frequency-dependent measure for the linear dependency between two stationary processes, and the recent literature contain several contributions on how to form high-resolution data-dependent and adaptive MSC estimators, and on the efficient implementation of such estimators. In this work, we further this development with the presentation of computationally efficient implementations of the recent iterative adaptive approach (IAA) estimator, present a novel sparse learning via iterative minimization (SLIM) algorithm, discuss extensions to two-dimensional data sets, examining both the case of complete data sets and when some of the observations are missing. The algorithms further the recent development of exploiting the estimators' inherently low displacement rank of the necessary products of Toeplitz-like matrices, extending these formulations to the coherence estimation using IAA and SLIM formulations. The performance of the proposed algorithms and implementations are illustrated both with theoretical complexity measures and with numerical simulations.
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| 3. |
- Babu, Prabhu, et al.
(författare)
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Connection between SPICE and Square-Root LASSO for sparse parameter estimation
- 2014
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 95, s. 10-14
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Tidskriftsartikel (refereegranskat)abstract
- In this note we show that the sparse estimation technique named Square-Root LASSO (SR-LASSO) is connected to a previously introduced method named SPICE. More concretely we prove that the SR-LASSO with a unit weighting factor is identical to SPICE. Furthermore we show via numerical simulations that the performance of the SR-LASSO changes insignificantly when the weighting factor is varied. SPICE stands for sparse iterative covariance-based estimation and LASSO for least absolute shrinkage and selection operator.
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| 4. |
- Burak Guldogan, Mehmet, et al.
(författare)
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Multipath channel identification by using global optimization in ambiguity function domain
- 2011
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Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 91:11, s. 2647-2660
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Tidskriftsartikel (refereegranskat)abstract
- A new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delay-Doppler domain by using the cross-ambiguity function (CAF) for efficient exploitation of the delay-Doppler diversity of the multipath components. Clusters of multipath components can be identified by using a simple amplitude thresholding in the delay-Doppler domain. Particle swarm optimization (PSO) can be used to identify parameters of the multipath components in each cluster. The performance of the proposed PSO-CAF technique is compared with the space alternating generalized expectation maximization (SAGE) technique and with a recently proposed PSO based technique at various SNR levels. Simulation results clearly quantify the superior performance of the PSO-CAF technique over the alternative techniques at all practically significant SNR levels.
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| 5. |
- Chung, P. J., et al.
(författare)
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Broadband ML estimation under model order uncertainty
- 2010
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 90:5, s. 1350-1356
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Tidskriftsartikel (refereegranskat)abstract
- The number of signals hidden in data plays a crucial role in array processing. When this information is not available, conventional approaches apply information theoretic criteria or multiple hypothesis tests to simultaneously estimate model order and parameter. These methods are usually computationally intensive, since ML estimates are required for a hierarchy of nested models. In this contribution, we propose a computationally efficient solution to avoid this full search procedure and address issues unique to the broadband case. Our max-search approach computes ML estimates only for the maximally hypothesized number of signals, and selects relevant components through hypothesis testing. Furthermore, we introduce a criterion based on the rank of the steering matrix to reduce indistinguishable components caused by overparameterization. Numerical experiments show that despite model order uncertainty, the proposed method achieves comparable estimation and detection accuracy as standard methods, but at much lower computational expense. (C) 2009 Elsevier B.V. All rights reserved.
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| 6. |
- Eghbali, Amir, et al.
(författare)
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A class of reconfigurable and low-complexity two-stage Nyquist filters
- 2014
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Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 96, s. 164-172
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Tidskriftsartikel (refereegranskat)abstract
- This paper introduces a class of reconfigurable two-stage Nyquist filters where the Farrow structure realizes the polyphase components of linear-phase finite-length impulse response (FIR) filters. By adjusting the variable predetermined multipliers of the Farrow structure, various linear-phase FIR Nyquist filters and integer interpolation/decimation structures are obtained, online. However, the filter design problem is solved only once, offline. Design examples, based on the reweighted l(1)-norm minimization, illustrate the proposed method. Savings in the arithmetic complexity are obtained when compared to the reconfigurable single-stage structures.
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| 7. |
- Eghbali, Amir, et al.
(författare)
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A method for the design of Farrow-structure based variable fractional-delay FIR filters
- 2013
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Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 93:5, s. 1341-1348
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes a method to design variable fractional-delay (FD) filters using the Farrow structure. In the transfer function of the Farrow structure, different subfilters are weighted by different powers of the FD value. As both the FD value and its powers are smaller than 0.5, our proposed method uses them as diminishing weighting functions. The approximation error, for each subfilter, is then increased in proportion to the power of the FD value. This gives a new distribution for the orders of the Farrow subfilters which has not been utilized before. This paper also includes these diminishing weighting functions in the filter design so as to obtain their optimal values, iteratively. We consider subfilters of both even and odd orders. Examples illustrate our proposed method and comparisons, to various earlier designs, show a reduction of the arithmetic complexity.
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| 8. |
- Eghbali, Amir, et al.
(författare)
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Conditions for Lth-band filters of order 2N as cascades of identical linear-phase FIR spectral factors of order N
- 2014
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Ingår i: Signal Processing. - : Elsevier. - 0165-1684 .- 1872-7557. ; 97:April
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents formulas for the number of optimization parameters (degrees of freedom) when designing Type I linear-phase finite-length impulse response (FIR) Lth-band filters of order 2N as cascades of identical linear-phase FIR spectral factors of order N. We deal with two types of degrees of freedom referred to as (i) the total degrees of freedom D-T, and (ii) the remaining degrees of freedom D-R. Due to the symmetries or antisymmetries in the impulse responses of the spectral factors, D-T roughly equals N/2. Some of these parameters are specifically needed to meet the Lth-band conditions because, in an Lth-band filter, every Lth coefficient is zero and the center tap equals 1/L. The remaining D-R parameters can then be used to improve the stopband characteristics of the overall Lth-band filter. We derive general formulas for D-R with given pairs of L and N. It is shown that for a fixed L, the choices of N, in a close neighborhood, may even decrease D-R despite increasing the arithmetic complexity, order, and the delay.
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| 9. |
- Glentis, George-Othan, et al.
(författare)
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SAR Imaging via Efficient Implementations of Sparse ML Approaches
- 2014
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684. ; 95:February, s. 15-26
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Tidskriftsartikel (refereegranskat)abstract
- High-resolution spectral estimation techniques are of notable interest for synthetic aperture radar (SAR) imaging. Several sparse estimation techniques have been shown to provide significant performance gains as compared to conventional approaches. We consider efficient implementation of the recent iterative sparse maximum likelihood-based approaches (SMLAs). Furthermore, we present approximative fast SMLA formulation using the Quasi-Newton approach, as well as consider hybrid SMLA-MAP algorithms. The effectiveness of the discussed techniques is illustrated using numerical and experimental examples.
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| 10. |
- Gudmundson, Erik, et al.
(författare)
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Blood velocity estimation using ultrasound and spectral iterative adaptive approaches
- 2011
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 91:5, s. 1275-1283
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes two novel iterative data-adaptive spectral estimation techniques for blood velocity estimation using medical ultrasound scanners. The techniques make no assumption on the sampling pattern of the emissions or the depth samples, allowing for duplex mode transmissions where B-mode images are interleaved with the Doppler emissions. Furthermore, the techniques are shown, using both simplified and more realistic Field II simulations as well as in vivo data, to outperform current state-of-the-art techniques, allowing for accurate estimation of the blood velocity spectrum using only 30% of the transmissions, thereby allowing for the examination of two separate vessel regions while retaining an adequate updating rate of the B-mode images. In addition, the proposed methods also allow for more flexible transmission patterns, as well as exhibit fewer spectral artifacts as compared to earlier techniques.
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