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Signal Processing Letters, IEEE

Issue 9 • Date Sept. 2010

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Displaying Results 1 - 14 of 14
  • [Front cover]

    Page(s): C1
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  • IEEE Signal Processing Letters publication information

    Page(s): C2
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  • Table of contents

    Page(s): 777 - 778
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  • Approximate SEP Analysis for DF Cooperative Networks With Opportunistic Relaying

    Page(s): 779 - 782
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (284 KB) |  | HTML iconHTML  

    We analyze the symbol error probability (SEP) performance of cooperative diversity networks with opportunistic decode-and-forward (ODF) relaying. Assuming that channels suffer from independent nonidentical Rayleigh fading and symbols are M-PSK modulated, the approximate closed-form SEP expressions are derived for opportunistic relaying with adaptive and fixed DF protocols, respectively. Simulations are carried out to validate the theoretical analysis. Results show that the derived approximate SEP is tight particularly at medium and high SNR. View full abstract»

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  • Comparison of Two Frame Rate Conversion Schemes for Reducing LCD Motion Blurs

    Page(s): 783 - 786
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (467 KB) |  | HTML iconHTML  

    Liquid crystal display (LCD) is known to have motion blur due to the slow response and sample-hold characteristics of the liquid crystal (LC). To alleviate the LCD motion blur, improving the LC response is the most fundamental solution. However, if the response time is shortened, then more frames are needed and hence frame rate up conversion (FRUC) should be used. In this paper, we study two FRUC methods. We compare the output signal qualities by studying the temporal and spatial profile of the two methods. We use the solution of Erickson-Leslie equation to derive the step response, in contrast to the existing literature where the resistor-capacitor (RC) approximation and uniform averaging function are used. The step response we derived is able to model not only the general trend of the rising and falling edges, but also the effects of different gray level transitions. Based on the step response, we analyze the two methods by comparing the observed signal in both the spatial and temporal domain. View full abstract»

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  • Model Based Motion Vector Predictor for Zoom Motion

    Page(s): 787 - 790
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (180 KB) |  | HTML iconHTML  

    As zoom motion is common in video applications, a linear motion model is derived to describe zoom motion based on the analyses of camera imaging principles. Based on the motion model, a motion vector predictor for videos involving zoom motion is proposed. A rate distortion (RD) criterion is used to choose the optimal motion vector predictor between the one utilized in H.264/AVC and the one derived from the linear motion model. Experimental results demonstrate that by implementing the proposed method into Key Technology Area test platform version 2.2r1(KTA2.2r1), the maximum and average bit rate savings can be achieved as high as 7.66% and 4.90% respectively, while maintaining the same quality of reconstructed videos. View full abstract»

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  • Adaptive Solution for Blind Equalization and Carrier-Phase Recovery of Square-QAM

    Page(s): 791 - 794
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (608 KB) |  | HTML iconHTML  

    In this letter, we adaptively optimize the equalizer output energy to obtain a joint blind equalization and carrier-phase recovery solution. The resulting (multimodulus) update algorithm possesses a particular zero-memory Bussgang-type nonlinearity. We provide evidence of good performance, in comparison to existing adaptive methods, like RCA, MMA and CMA, through computer simulations for higher-order quadrature amplitude modulation signalling on symbol- and fractionally-spaced channels. View full abstract»

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  • Parametric FIR Design of Propagation Loss Filters in Digital Waveguide String Models

    Page(s): 795 - 798
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (279 KB) |  | HTML iconHTML  

    One of the attractive features of sound synthesis by physical modeling is the potential to build acoustic-sounding digital instruments that offer more flexibility and different options in its design and control than their real-life counterparts. In order to develop such virtual-acoustic instruments, the models they are based on need to be fully parametric, i.e., all coefficients employed in the model are functions of physical parameters that are controlled either online or at the (offline) design stage. In this letter we show how propagation losses can be parametrically incorporated in digital waveguide string models with the use of zero-phase FIR filters. Starting from the simplest possible design in the form of a three-tap FIR filter, a higher-order FIR strategy is presented and discussed within the perspective of string sound synthesis with digital waveguide models. View full abstract»

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  • Blind Source Separation by Fully Nonnegative Constrained Iterative Volume Maximization

    Page(s): 799 - 802
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (796 KB) |  | HTML iconHTML  

    Blind source separation (BSS) has been widely discussed in many real applications. Recently, under the assumption that both of the sources and the mixing matrix are nonnegative, Wang develop an amazing BSS method by using volume maximization. However, the algorithm that they have proposed can guarantee the nonnegativities of the sources only, but cannot obtain a nonnegative mixing matrix necessarily. In this letter, by introducing additional constraints, a method for fully nonnegative constrained iterative volume maximization (FNCIVM) is proposed. The result is with more interpretation, while the algorithm is based on solving a single linear programming problem. Numerical experiments with synthetic signals and real-world images are performed, which show the effectiveness of the proposed method. View full abstract»

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  • Locally Affine Invariant Descriptors for Shape Matching and Retrieval

    Page(s): 803 - 806
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (233 KB) |  | HTML iconHTML  

    This work proposes novel locally affine invariant descriptors for shape representation. The descriptors are theoretically simple and solid, derived from the matrix theories. They can be used for matching and retrieval of shapes under affine transformation, articulated motion or nonrigid deformation. Comparisons of the work with the state-of-the-art shape descriptors are performed based on synthetic and some well-known databases. The experiments validate that the proposed descriptors achieve higher retrieval accuracy and have faster running speed than most of other approaches. View full abstract»

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  • Sigma Set Based Implicit Online Learning for Object Tracking

    Page(s): 807 - 810
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB) |  | HTML iconHTML  

    This letter presents a novel object tracking approach within the Bayesian inference framework through implicit online learning. In our approach, the target is represented by multiple patches, each of which is encoded by a powerful and efficient region descriptor called Sigma set. To model each target patch, we propose to utilize the online one-class support vector machine algorithm, named Implicit online Learning with Kernels Model (ILKM). ILKM is simple, efficient, and capable of learning a robust online target predictor in the presence of appearance changes. Responses of ILKMs related to multiple target patches are fused by an arbitrator with an inference of possible partial occlusions, to make the decision and trigger the model update. Experimental results demonstrate that the proposed tracking approach is effective and efficient in ever-changing and cluttered scenes. View full abstract»

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  • Minimax Robust Optimal Estimation Fusion in Distributed Multisensor Systems With Uncertainties

    Page(s): 811 - 814
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (140 KB) |  | HTML iconHTML  

    In this paper, the robust estimation fusion problem in multisensor systems with norm-bounded uncertainties concerning the error covariance matrix between local estimates is addressed. A robust fusion method by minimizing the worst-case fused mean-squared error (MSE) for all feasible error covariance matrices of local estimates is proposed. The minimax robust fusion weighting matrices can be explicitly formulated as a function of solution of a semidefinite programming (SDP). Some numerical examples demonstrate that when the error covariance matrix suffers disturbance, the proposed fusion method is more robust than the nominal fusion method which ignores the uncertainties, and can improve the performance when the disturbance is considerably large. View full abstract»

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  • IEEE Signal Processing Letters Information for authors

    Page(s): 815 - 816
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  • IEEE Signal Processing Society Information

    Page(s): C3
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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
Peter Willett
University of Connecticut
Storrs, CT 06269
peter.willett@uconn.edu