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IEEE Signal Processing Letters

Issue 9 • Sept. 2012

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Displaying Results 1 - 19 of 19
  • [Front cover]

    Publication Year: 2012, Page(s): C1
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  • IEEE Signal Processing Letters publication information

    Publication Year: 2012, Page(s): C2
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  • Table of contents

    Publication Year: 2012, Page(s):549 - 550
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  • On the Exponentially Embedded Family (EEF) Rule for Model Order Selection

    Publication Year: 2012, Page(s):551 - 554
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (768 KB) | HTML iconHTML

    Model selection is an important task in many signal processing applications. In this letter, we present a generalized likelihood ratio (GLR)-based derivation of the recently proposed EEF rule in an attempt to cast EEF in the main stream of model order selection approaches and provide further insights into its theoretical foundations. We also show that EEF can be expected to behave asymptotically (... View full abstract»

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  • Explicit Coherence Enhancing Filter With Spatial Adaptive Elliptical Kernel

    Publication Year: 2012, Page(s):555 - 558
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (915 KB) | HTML iconHTML

    The goal of this letter is to provide an elliptical filter to improve image coherence for the task of image smoothing and inpainting. The kernel of this filter is adaptively weighted and its shape is determined by local coherence estimation. The long axis of its ellipse is the same as the coherence direction and we put more weight there to enhance coherence. Compared with the related anisotropic p... View full abstract»

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  • A Harmonic-Based Biologically Inspired Approach to Monaural Speech Separation

    Publication Year: 2012, Page(s):559 - 562
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (633 KB) | HTML iconHTML

    This letter proposes a computational auditory scene analysis (CASA) model for monaural speech separation. In this model, we integrate three biologically inspired approaches for: auditory spectrogram generation, analysis of its spectro-temporal content, and tracking its harmonic structure. In a top-down process, the estimated ideal binary mask (EIBM) is calculated using the spectral amplitude of th... View full abstract»

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  • A Distributed and Scalable Processing Method Based Upon ADMM

    Publication Year: 2012, Page(s):563 - 566
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1416 KB) | HTML iconHTML

    The alternating direction multiplier method (ADMM) was originally devised as an iterative method for solving convex minimization problems by means of parallelization, and was recently used for distributed processing. This letter proposes a modification of state-of-the-art ADMM formulations in order to obtain a scalable version, well suited for a wide range of applications such as cooperative local... View full abstract»

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  • Blind Source Separation Using Decoupled Relative Newton Algorithm

    Publication Year: 2012, Page(s):567 - 570
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1198 KB) | HTML iconHTML

    A decoupled relative Newton algorithm is proposed for the matrix optimization problem encountered in blind source separation (BSS) and independent component analysis (ICA). The algorithm decouples the matrix optimization problem into a series of small vector optimization problems. The nonsingularity of separation matrix enables a simple and efficient relative Newton learning algorithm for the vect... View full abstract»

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  • Modular Weighted Global Sparse Representation for Robust Face Recognition

    Publication Year: 2012, Page(s):571 - 574
    Cited by:  Papers (18)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (625 KB) | HTML iconHTML

    This work proposes a novel framework of robust face recognition based on the sparse representation. Image is first divided into modules and each module is processed separately to determine its reliability. A reconstructed image from the modules weighted by their reliability is formed for the robust recognition. We propose to use the modular sparsity and residual jointly to determine the modular re... View full abstract»

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  • Linear Subclass Support Vector Machines

    Publication Year: 2012, Page(s):575 - 578
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1019 KB) | HTML iconHTML

    In this letter, linear subclass support vector machines (LSSVMs) are proposed that can efficiently learn a piecewise linear decision function for binary classification problems. This is achieved using a nongaussianity criterion to derive the subclass structure of the data, and a new formulation of the optimization problem that exploits the subclass information. LSSVMs provide low computation cost ... View full abstract»

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  • Nonlinear Phase Retrieval Using Projection Operator and Iterative Wavelet Thresholding

    Publication Year: 2012, Page(s):579 - 582
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (847 KB) | HTML iconHTML

    With hard X-rays synchrotron beams, phase contrast can be obtained with the measurement of the Fresnel diffraction intensity patterns associated to a phase shift induced by the object. We have studied the resolution of this inverse problem with an iterative thresholding algorithm in wavelet coordinates combined with an iterative nonlinear method with a Tikhonov regularization and projection operat... View full abstract»

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  • A Family of Fast Hadamard–Fourier Transform Algorithms

    Publication Year: 2012, Page(s):583 - 586
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1064 KB) | HTML iconHTML

    In this letter, we present a family of fast Hadamard-Fourier transform algorithms which combined Walsh Hadamard and discrete Fourier transforms into one single algorithm. These family algorithms can be computed in butterfly structure, and have similar sparse matrix factorization in each stage, and have less computation stages than the sum of Walsh Hadamard and discrete Fourier transforms. We facto... View full abstract»

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  • Persymmetric Rao and Wald Tests for Partially Homogeneous Environment

    Publication Year: 2012, Page(s):587 - 590
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1118 KB) | HTML iconHTML

    This letter deals with the problem of adaptive detection in partially-homogeneous Gaussian disturbance with unknown but persymmetric structured covariance matrix. Since no uniformly most powerful test exists for the problem at hand, we devise and assess two detection strategies based on the Rao test and the Wald test design criteria. Remarkably, both detectors ensure the constant false alarm rate ... View full abstract»

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  • IEEE Signal Processing Letters information for authors

    Publication Year: 2012, Page(s):591 - 592
    Request permission for commercial reuse | PDF file iconPDF (134 KB)
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  • IEEE Signal Processing Letters EDICS

    Publication Year: 2012, Page(s): 593
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  • Renew your IEEE membership for 2012 and add Signal Processing Society

    Publication Year: 2012, Page(s): 594
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  • Order form for reprints

    Publication Year: 2012, Page(s): 596
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  • IEEE Signal Processing Society Information

    Publication Year: 2012, Page(s): C3
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  • [Blank page - Back cover]

    Publication Year: 2012, Page(s): C4
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Aims & Scope

The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
James E. Fowler
Dept Electrical & Computer Engineering
Associate Director                         
Distributed Analytics and Security Institute
Mississippi State University
Mississippi State, MS 39762 USA
fowler@ece.msstate.edu