# IEEE Journal of Selected Topics in Signal Processing

## Filter Results

Displaying Results 1 - 25 of 28

Publication Year: 2007, Page(s):C1 - C4
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• ### IEEE Journal of Selected Topics in Signal Processing publication information

Publication Year: 2007, Page(s): C2
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• ### <newline/>Introduction to the Issue on Convex Optimization Methods for Signal Processing

Publication Year: 2007, Page(s):537 - 539
Cited by:  Papers (2)
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• ### Stable Convergence Behavior Under Summable Perturbations of a Class of Projection Methods for Convex Feasibility and Optimization Problems

Publication Year: 2007, Page(s):540 - 547
Cited by:  Papers (51)  |  Patents (2)
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We study the convergence behavior of a class of projection methods for solving convex feasibility and optimization problems. We prove that the algorithms in this class converge to solutions of the consistent convex feasibility problem, and that their convergence is stable under summable perturbations. Our class is a subset of the class of string-averaging projection methods, large enough to contai... View full abstract»

• ### Configuring Competing Classifier Chains in Distributed Stream Mining Systems

Publication Year: 2007, Page(s):548 - 563
Cited by:  Papers (11)  |  Patents (1)
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Networks of classifiers are capturing the attention of system and algorithmic researchers because they offer improved accuracy over single model classifiers, can be distributed over a network of servers for improved scalability, and can be adapted to available system resources. In this paper, we develop algorithms to optimally configure networks (chains) of such classifiers given system processing... View full abstract»

• ### A Douglas–Rachford Splitting Approach to Nonsmooth Convex Variational Signal Recovery

Publication Year: 2007, Page(s):564 - 574
Cited by:  Papers (216)
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Under consideration is the large body of signal recovery problems that can be formulated as the problem of minimizing the sum of two (not necessarily smooth) lower semicontinuous convex functions in a real Hilbert space. This generic problem is analyzed and a decomposition method is proposed to solve it. The convergence of the method, which is based on the Douglas-Rachford algorithm for monotone o... View full abstract»

• ### A Sparsity-Based Method for the Estimation of Spectral Lines From Irregularly Sampled Data

Publication Year: 2007, Page(s):575 - 585
Cited by:  Papers (55)
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We address the problem of estimating spectral lines from irregularly sampled data within the framework of sparse representations. Spectral analysis is formulated as a linear inverse problem, which is solved by minimizing an l<sup>1</sup>-norm penalized cost function. This approach can be viewed as a basis pursuit de-noising (BPDN) problem using a dictionary of cisoids with high frequen... View full abstract»

• ### Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems

Publication Year: 2007, Page(s):586 - 597
Cited by:  Papers (1500)  |  Patents (36)
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Many problems in signal processing and statistical inference involve finding sparse solutions to under-determined, or ill-conditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ) error term combined with a sparseness-inducing regularization term. Basis pursuit, the least absolute shrinkage and selection operato... View full abstract»

• ### Convergence of a Sparse Representations Algorithm Applicable to Real or Complex Data

Publication Year: 2007, Page(s):598 - 605
Cited by:  Papers (24)
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Sparse representations has become an important topic in years. It consists in representing, say, a signal (vector) as a linear combination of as few as possible components (vectors) from a redundant basis (of the vector space). This is usually performed, either iteratively (adding a component at a time), or globally (selecting simultaneously all the needed components). We consider a specific algor... View full abstract»

• ### An Interior-Point Method for Large-Scale$\ell_1$-Regularized Least Squares

Publication Year: 2007, Page(s):606 - 617
Cited by:  Papers (1009)  |  Patents (5)
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Recently, a lot of attention has been paid to regularization based methods for sparse signal reconstruction (e.g., basis pursuit denoising and compressed sensing) and feature selection (e.g., the Lasso algorithm) in signal processing, statistics, and related fields. These problems can be cast as -regularized least-squares programs (LSPs), which can be reformulated as convex quadratic programs, and... View full abstract»

• ### Robust Predictive Quantization: Analysis and Design Via Convex Optimization

Publication Year: 2007, Page(s):618 - 632
Cited by:  Papers (29)
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Predictive quantization is a simple and effective method for encoding slowly-varying signals that is widely used in speech and audio coding. It has been known qualitatively that leaving correlation in the encoded samples can lead to improved estimation at the decoder when encoded samples are subject to erasure. However, performance estimation in this case has required Monte Carlo simulation. Provi... View full abstract»

• ### Design of an Optimal Two-Channel Orthogonal Cyclic Filterbank Using Semidefinite Programming

Publication Year: 2007, Page(s):633 - 640
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A simple method for the design of an optimal two-channel orthogonal cyclic filterbank using semidefinite programming is presented. The criterion for optimality is to maximize the passband energy, or equivalently, to minimize the stopband energy of the filter's impulse response. The objective function and orthogonality constraints are represented in terms of the cyclic autocorrelation sequence of t... View full abstract»

• ### Multidimensional FIR Filter Design Via Trigonometric Sum-of-Squares Optimization

Publication Year: 2007, Page(s):641 - 650
Cited by:  Papers (8)
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We discuss a method for multidimensional FIR filter design via sum-of-squares formulations of spectral mask constraints. The sum-of-squares optimization problem is expressed as a semidefinite program with low-rank structure, by sampling the constraints using discrete cosine and sine transforms. The resulting semidefinite program is then solved by a customized primal-dual interior-point method that... View full abstract»

Publication Year: 2007, Page(s):651 - 659
Cited by:  Papers (4)
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In this paper, we study the tradeoffs among three main criteria for adaptive beamformer design: maximal signal-to-interference-plus-noise ratio (MSINR), minimal mean-squared error (MMSE), and minimal least-squares error (MLSE). When the power and steering vector of the signal-of-interest (SOI) are exactly known, there are beamformers that can simultaneously meet the MMSE and MSINR criteria. Howeve... View full abstract»

• ### Optimal Array-Pattern Synthesis for Wideband Digital Transmit Arrays

Publication Year: 2007, Page(s):660 - 677
Cited by:  Papers (17)
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Some next-generation radio frequency systems are expected to share a common transmit aperture among multiple users across a wide range of frequencies and functions such as radar and communications. The requisite linear architectures and digital signal generation will permit far greater flexibility in the design of array patterns than traditional time-delay steered wideband transmit arrays. Merely ... View full abstract»

• ### Robust Calibration of an Improved Delta-Sigma Data Converter Using Convex Optimization

Publication Year: 2007, Page(s):678 - 685
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In this paper, we analyze that analog circuit imperfections in the cascaded delta-sigma modulators may lead to the incomplete noise cancellation from the earlier stages, as well as non-unit transfer function from the input signal to the output, resulting in the degradation of signal-to-noise ratio (SNR) performance. It is difficult to design one digital filter to compensate the effects from both t... View full abstract»

• ### Optimized Resource Allocation for Upstream Vectored DSL Systems With Zero-Forcing Generalized Decision Feedback Equalizer

Publication Year: 2007, Page(s):686 - 699
Cited by:  Papers (20)  |  Patents (1)
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In upstream vectored DSL systems using zero-forcing generalized decision feedback equalizers (ZF-GDFE), different decoding orders cause performance tradeoffs among the users. In this paper, these tradeoffs are characterized by formulating optimization problems with practical constraints. Lagrange dual decomposition and a two-step algorithm are used to solve the dual problems optimally with the com... View full abstract»

• ### Robust Wireless Relay Networks: Slow Power Allocation With Guaranteed QoS

Publication Year: 2007, Page(s):700 - 713
Cited by:  Papers (55)
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In wireless networks, power allocation is an effective technique for prolonging network lifetime, achieving better quality-of-service (QoS), and reducing network interference. However, these benefits depend on knowledge of the channel state information (CSI), which is hardly perfect. Therefore, robust algorithms that take into account such CSI uncertainties play an important role in the design of ... View full abstract»

• ### Convex Conic Formulations of Robust Downlink Precoder Designs With Quality of Service Constraints

Publication Year: 2007, Page(s):714 - 724
Cited by:  Papers (115)
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We consider the design of linear precoders (beamformers) for broadcast channels with Quality of Service (QoS) constraints for each user, in scenarios with uncertain channel state information (CSI) at the transmitter. We consider a deterministically-bounded model for the channel uncertainty of each user, and our goal is to design a robust precoder that minimizes the total transmission power require... View full abstract»

• ### Optimal Matching in Wireless Sensor Networks

Publication Year: 2007, Page(s):725 - 735
Cited by:  Papers (15)
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We design a wireless sensor network (WSN) in terms of rate and power allocation in order to send without loss the data gathered by the nodes to a common sink. Correlation between the data and channel impairments dictate the constraints of the optimization problem. We further assume that the WSN uses off-the-shelf compression and channel coding algorithms. More precisely source and channel coding a... View full abstract»

• ### List of Reviewers

Publication Year: 2007, Page(s):736 - 737
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• ### IEEE Journal of Selected Topics in Signal Processing Information for authors

Publication Year: 2007, Page(s): 738
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• ### Special issue on fMRI analysis for human brain mapping

Publication Year: 2007, Page(s): 739
| PDF (130 KB)
• ### Special issue on digital image processing techniques for oncology

Publication Year: 2007, Page(s): 740
| PDF (124 KB)
• ### Special issue on visual media quality assessment

Publication Year: 2007, Page(s): 741
| PDF (172 KB)

## Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief

Shrikanth (Shri) S. Narayanan
Viterbi School of Engineering
University of Southern California
Los Angeles, CA 90089 USA
shri@sipi.usc.edu