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Sökning: L773:1941 0476 OR L773:1053 587X

  • Resultat 1-10 av 553
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1.
  • Abeynanda, Hansi, et al. (författare)
  • On the Primal Feasibility in Dual Decomposition Methods Under Additive and Bounded Errors
  • 2023
  • Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 71, s. 655-669
  • Tidskriftsartikel (refereegranskat)abstract
    • With the unprecedented growth of signal processing and machine learning application domains, there has been a tremendous expansion of interest in distributed optimization methods to cope with the underlying large-scale problems. Nonetheless, inevitable system-specific challenges such as limited computational power, limited communication, latency requirements, measurement errors, and noises in wireless channels impose restrictions on the exactness of the underlying algorithms. Such restrictions have appealed to the exploration of algorithms' convergence behaviors under inexact settings. Despite the extensive research conducted in the area, it seems that the analysis of convergences of dual decomposition methods concerning primal optimality violations, together with dual optimality violations is less investigated. Here, we provide a systematic exposition of the convergence of feasible points in dual decomposition methods under inexact settings, for an important class of global consensus optimization problems. Convergences and the rate of convergences of the algorithms are mathematically substantiated, not only from a dual-domain standpoint but also from a primal-domain standpoint. Analytical results show that the algorithms converge to a neighborhood of optimality, the size of which depends on the level of underlying distortions.
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2.
  • Adalbjornsson, S. I., et al. (författare)
  • Estimating Periodicities in Symbolic Sequences Using Sparse Modeling
  • 2015
  • Ingår i: Ieee Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 63:8, s. 2142-2150
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, we propose a method for estimating statistical periodicities in symbolic sequences. Different from other common approaches used for the estimation of periodicities of sequences of arbitrary, finite, symbol sets, that often map the symbolic sequence to a numerical representation, we here exploit a likelihood-based formulation in a sparse modeling framework to represent the periodic behavior of the sequence. The resulting criterion includes a restriction on the cardinality of the solution; two approximate solutions are suggested-one greedy and one using an iterative convex relaxation strategy to ease the cardinality restriction. The performance of the proposed methods are illustrated using both simulated and real DNA data, showing a notable performance gain as compared to other common estimators.
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3.
  • Alam, Syed Asad, 1984-, et al. (författare)
  • On the implementation of time-multiplexed frequency-response masking filters
  • 2016
  • Ingår i: IEEE Transactions on Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-587X .- 1941-0476. ; 64:15, s. 3933-3944
  • Tidskriftsartikel (refereegranskat)abstract
    • The complexity of narrow transition band finite-length impulse response (FIR) filters is high and can be reduced by using frequency-response masking (FRM) techniques. These techniques use a combination of periodic model and, possibly periodic, masking filters. Time-multiplexing is in general beneficial since only rarely does the technology bound maximum obtainable clock frequency and the application determined required sample rate correspond. Therefore, architectures for time-multiplexed FRM filters that benefit from the inherent sparsity of theperiodic filters are introduced in this work.We show that FRM filters not only reduces the number of multipliers needed, but also have benefits in terms of memory usage. Despite the total amount of samples to be stored is larger for FRM, it results in fewer memory resources needed in FPGAs and more energy efficient memory schemes in ASICs. In total, the power consumption is significantly reduced compared to a single stage implementation. Furthermore, we show that the choice of the interpolation factor which gives the least complexity for the periodic model filter and subsequent masking filter(s) is a function of the time-multiplexing factor, meaning that the minimum number of multipliers not always correspond to the minimum number of multiplications. Both single-port and dual-port memories are considered and the involved trade-off in number of multipliers and memory complexity is illustrated. The results show that for FPGA implementation, the power reduction ranges from 23% to 68% for the considered examples.
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4.
  • Alenlöv, Johan, et al. (författare)
  • Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models
  • 2019
  • Ingår i: IEEE Transactions on Signal Processing. - : IEEE. - 1053-587X .- 1941-0476. ; 67:21, s. 5571-5582
  • Tidskriftsartikel (refereegranskat)abstract
    • We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one for each marginal, in resemblance with the so-called particle-based, rapid incremental smoother (PaRIS). Each estimator is propagated until a stopping criterion, measuring the fluctuations of the estimates, is met. The presented algorithm is furnished with theoretical results describing its asymptotic limit and memory usage.
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5.
  • Alodeh, Maha, et al. (författare)
  • Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels
  • 2015
  • Ingår i: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 63:6, s. 1404-1418
  • Tidskriftsartikel (refereegranskat)abstract
    • This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and least squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas.
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6.
  • Ambat, Sooraj K., et al. (författare)
  • A Committee Machine Approach for Compressed Sensing Signal Reconstruction
  • 2014
  • Ingår i: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 62:7, s. 1705-1717
  • Tidskriftsartikel (refereegranskat)abstract
    • Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.
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7.
  • Ambat, Sooraj K., et al. (författare)
  • Fusion of Algorithms for Compressed Sensing
  • 2013
  • Ingår i: IEEE Transactions on Signal Processing. - 1053-587X .- 1941-0476. ; 61:14, s. 3699-3704
  • Tidskriftsartikel (refereegranskat)abstract
    • For compressed sensing (CS), we develop a new scheme inspired by data fusion principles. In the proposed fusion based scheme, several CS reconstruction algorithms participate and they are executed in parallel, independently. The final estimate of the underlying sparse signal is derived by fusing the estimates obtained from the participating algorithms. We theoretically analyze this fusion based scheme and derive sufficient conditions for achieving a better reconstruction performance than any participating algorithm. Through simulations, we show that the proposed scheme has two specific advantages: 1) it provides good performance in a low dimensional measurement regime, and 2) it can deal with different statistical natures of the underlying sparse signals. The experimental results on real ECG signals shows that the proposed scheme demands fewer CS measurements for an approximate sparse signal reconstruction.
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8.
  • Andersson Naesseth, Christian, et al. (författare)
  • High-Dimensional Filtering Using Nested Sequential Monte Carlo
  • 2019
  • Ingår i: IEEE Transactions on Signal Processing. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1053-587X .- 1941-0476. ; 67:16, s. 4177-4188
  • Tidskriftsartikel (refereegranskat)abstract
    • Sequential Monte Carlo (SMC) methods comprise one of the most successful approaches to approximate Bayesian filtering. However, SMC without a good proposal distribution can perform poorly, in particular in high dimensions. We propose nested sequential Monte Carlo, a methodology that generalizes the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correctSMCalgorithm. This way, we can compute an "exact approximation" of, e. g., the locally optimal proposal, and extend the class of models forwhichwe can perform efficient inference using SMC. We showimproved accuracy over other state-of-the-art methods on several spatio-temporal state-space models.
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9.
  • Arghavani, Abbas, et al. (författare)
  • Covert Outage Minimization in the Presence of Multiple Wardens
  • 2023
  • Ingår i: IEEE Transactions on Signal Processing. - : IEEE. - 1053-587X .- 1941-0476. ; 71, s. 686-700
  • Tidskriftsartikel (refereegranskat)abstract
    • The idea of covert communication is to conceal the presence of a transmission from an illegitimate receiver, known as a warden. This paper tackles the problem of finite blocklength covert communication in the presence of multiple colluding wardens. The system consists of Alice, who aims to covertly transmit to Bob with the help of a cooperative jammer (henceforth known as Jammer), and a Fusion Center (FC) in charge of combining the wardens' information and deciding on the presence of Alice's transmission accordingly. In our proposed approach, we utilize a two-player zero-sum game to model the interaction between Alice and Jammer jointly as one player and FC as the second player. In this game, Alice and Jammer cooperatively randomize over a range of transmitting and jamming powers to confuse FC. In contrast, FC randomly changes the detection threshold to confuse Alice. The main focus of the paper is to study the impact of employing multiple wardens on the trade-off between the probability of error at FC and the outage probability at Bob. We derive a pay-off function that can be efficiently computed using linear programming to find the optimal distributions of transmitting and jamming powers as well as thresholds used by FC. The benefit of using a cooperative jammer in neutralizing the advantage of employing multiple wardens is shown by analytical results and numerical simulations.
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10.
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