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Selected Topics in Signal Processing, IEEE Journal of

Issue 4 • Date Aug. 2013

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Displaying Results 1 - 25 of 26
  • Table of contents

    Publication Year: 2013 , Page(s): C1 - C4
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  • IEEE Journal of Selected Topics in Signal Processing publication information

    Publication Year: 2013 , Page(s): C2
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  • Introduction to the issue on differential geometry in signal processing

    Publication Year: 2013 , Page(s): 573 - 575
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  • Minkovskian Gradient for Sparse Optimization

    Publication Year: 2013 , Page(s): 576 - 585
    Cited by:  Papers (1)
    Save to Project icon | Click to expandAbstract | PDF file iconPDF (2446 KB) |  | HTML iconHTML  

    Information geometry is used to elucidate convex optimization problems under L1 constraint. A convex function induces a Riemannian metric and two dually coupled affine connections in the manifold of parameters of interest. A generalized Pythagorean theorem and projection theorem hold in such a manifold. An extended LARS algorithm, applicable to both under-determined and over-determined ... View full abstract»

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  • Learning Ancestral Atom via Sparse Coding

    Publication Year: 2013 , Page(s): 586 - 594
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2646 KB) |  | HTML iconHTML  

    Sparse signal models have been the focus of recent research. In sparse coding, signals are represented with a linear combination of a small number of elementary signals called atoms, and the collection of atoms is called a dictionary. Design of the dictionary has strong influence on the signal approximation performance. Recently, to put prior information into dictionary learning, several methods i... View full abstract»

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  • Riemannian Medians and Means With Applications to Radar Signal Processing

    Publication Year: 2013 , Page(s): 595 - 604
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3750 KB) |  | HTML iconHTML  

    We develop a new geometric approach for high resolution Doppler processing based on the Riemannian geometry of Toeplitz covariance matrices and the notion of Riemannian p -means. This paper summarizes briefly our recent work in this direction. First of all, we introduce radar data and the problem of target detection. Then we show how to transform the original radar data into Toeplitz covari... View full abstract»

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  • Spinor Fourier Transform for Image Processing

    Publication Year: 2013 , Page(s): 605 - 613
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3574 KB) |  | HTML iconHTML  

    We propose in this paper to introduce a new spinor Fourier transform for both gray-level and color image processing. Our approach relies on the three following considerations: mathematically speaking, defining a Fourier transform requires to deal with group actions; vectors of the acquisition space can be considered as generalized numbers when embedded in a Clifford algebra; the tangent space of t... View full abstract»

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  • Robust Independent Component Analysis via Minimum \gamma -Divergence Estimation

    Publication Year: 2013 , Page(s): 614 - 624
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (5821 KB) |  | HTML iconHTML  

    Independent component analysis (ICA) has been shown to be useful in many applications. However, most ICA methods are sensitive to data contamination. In this article we introduce a general minimum U-divergence framework for ICA, which covers some standard ICA methods as special cases. Within the U-family we further focus on the γ-divergence due to its desirable property of super robustness ... View full abstract»

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  • Existence and Uniqueness of Hyperhelical Array Manifold Curves

    Publication Year: 2013 , Page(s): 625 - 633
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1855 KB) |  | HTML iconHTML  

    A number of significant problems, arising frequently in array signal processing, have been successfully tackled using methods based on the concept of the array manifold. These approaches take advantage of the inherent information about the array system which is encapsulated in the geometry of the array manifold. Array ambiguities, array uncertainties, array design and performance characterization ... View full abstract»

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  • Newton Algorithms for Riemannian Distance Related Problems on Connected Locally Symmetric Manifolds

    Publication Year: 2013 , Page(s): 634 - 645
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (4178 KB) |  | HTML iconHTML  

    The squared distance function is one of the standard functions on which an optimization algorithm is commonly run, whether it is used directly or chained with other functions. Illustrative examples include center of mass computation, implementation of k-means algorithm and robot positioning. This function can have a simple expression (as in the Euclidean case), or it might not even have a closed f... View full abstract»

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  • Frenet-Serret and the Estimation of Curvature and Torsion

    Publication Year: 2013 , Page(s): 646 - 654
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2929 KB) |  | HTML iconHTML  

    In this paper we approach the problem of analyzing space-time curves. In terms of classical geometry, the characterization of space-curves can be summarized in terms of a differential equation involving functional parameters curvature and torsion whose origins are from the Frenet-Serret framework. In particular, curvature measures the rate of change of the angle which nearby tangents make with the... View full abstract»

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  • Riemannian Distances for Signal Classification by Power Spectral Density

    Publication Year: 2013 , Page(s): 655 - 669
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3721 KB) |  | HTML iconHTML  

    Signal classification is an important issue in many branches of science and engineering. In signal classification, a feature of the signals is often selected for similarity comparison. A distance metric must then be established to measure the dissimilarities between different signal features. Due to the natural characteristics of dynamic systems, the power spectral density (PSD) of a signal is oft... View full abstract»

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  • Array Manifold Curves in {Fraktur {C}}^{N} and Their Complex Cartan Matrix

    Publication Year: 2013 , Page(s): 670 - 680
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2290 KB) |  | HTML iconHTML  

    The differential geometry of array manifold curves has been investigated extensively in the literature, leading to numerous applications. However, the existing differential geometric framework restricts the Cartan matrix to be purely real and so the vectors of the moving frame BBU(s) are found to be orthogonal only in the wide sense (i.e. only the real part of their inner product is equal to zero)... View full abstract»

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  • A Primer on Stochastic Differential Geometry for Signal Processing

    Publication Year: 2013 , Page(s): 681 - 699
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3503 KB) |  | HTML iconHTML  

    This primer explains how continuous-time stochastic processes (precisely, Brownian motion and other Itô diffusions) can be defined and studied on manifolds. No knowledge is assumed of either differential geometry or continuous-time processes. The arguably dry approach is avoided of first introducing differential geometry and only then introducing stochastic processes; both areas are motiva... View full abstract»

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  • Exploiting Information Geometry to Improve the Convergence Properties of Variational Active Contours

    Publication Year: 2013 , Page(s): 700 - 707
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1744 KB) |  | HTML iconHTML  

    In this paper we seek to exploit information geometry in order to define the Riemannian structure of the statistical manifold associated with the Chan-Vese active contour model. This Riemannian structure is obtained through a relationship between the contour's Mumford-Shah energy functional and the likelihood of the categorical latent variables of a Gaussian mixture model. Accordingly the natural ... View full abstract»

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  • Signal Detection on Euclidean Groups: Applications to DNA Bends, Robot Localization, and Optical Communication

    Publication Year: 2013 , Page(s): 708 - 719
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2411 KB) |  | HTML iconHTML  

    Three problems from disparate application areas are presented and solved here using a unified framework: 1) estimating the bend angle induced in DNA by a bound ligand such as a transcription factor or anti-cancer drug; 2) determining the intent of a mobile robot by observing its trajectories corrupted by environmental noise; 3) estimating the bit-error probability function associated with phase no... View full abstract»

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  • Stable Manifold Embeddings With Structured Random Matrices

    Publication Year: 2013 , Page(s): 720 - 730
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2715 KB) |  | HTML iconHTML  

    The fields of compressed sensing (CS) and matrix completion have shown that high-dimensional signals with sparse or low-rank structure can be effectively projected into a low-dimensional space (for efficient acquisition or processing) when the projection operator achieves a stable embedding of the data by satisfying the Restricted Isometry Property (RIP). It has also been shown that such stable em... View full abstract»

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  • IEEE Journal of Selected Topics in Signal Processing information for authors

    Publication Year: 2013 , Page(s): 731 - 732
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  • J-STSP call for special issue proposals

    Publication Year: 2013 , Page(s): 733
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  • Call for papers special issue on perception inspired video processing

    Publication Year: 2013 , Page(s): 734
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  • Special issue on signal processing for large-scale mimo communications

    Publication Year: 2013 , Page(s): 735
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  • Special issue on signal processing for social networks

    Publication Year: 2013 , Page(s): 736
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  • Special issue on signal processing in smart electric power grid

    Publication Year: 2013 , Page(s): 737
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  • Special issue on visual signal processing for wireless networks

    Publication Year: 2013 , Page(s): 738
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  • 2013 IEEE membership application

    Publication Year: 2013 , Page(s): 739 - 740
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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
Fernando Pereira
Instituto Superior Técnico