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Signal Processing Letters, IEEE

Issue 6 • Date June 2010

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Displaying Results 1 - 25 of 29
  • [Front cover]

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

    Page(s): C2
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    Freely Available from IEEE
  • Table of contents

    Page(s): 525 - 526
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    Freely Available from IEEE
  • Relationships Between \Psi _{ {\tt B}} -Energy Operator and Some Time-Frequency Representations

    Page(s): 527 - 530
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (261 KB) |  | HTML iconHTML  

    ΨB operator is an energy operator that measures the interactions between two complex signals. In this letter, new properties of ΨB operator are presented. Connections between ΨB operator and some time-frequency representations (cross-ambiguity function, short-time Fourier transform, Zak transform, and Gabor coefficients) are established. Link between ΨB operator of two input signals and their cross-spectrum is also derived. For two equal input signals, we find that Fourier transform of ΨB operator is proportional to the second derivative of the ambiguity function. The established links show the ability of ΨB operator to analyze nonstationary signals. A numerical example is provided for illustrating how to estimate the second order moment, of a FM signal, using ΨB operator. We compare the result to the moment given by the Wigner Ville distribution. View full abstract»

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  • Performance Analysis of Partial Relay Selection With Feedback Delay

    Page(s): 531 - 534
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (167 KB) |  | HTML iconHTML  

    We analyze the impact of outdated channel state information due to feedback delay on the performance of amplify-and-forward relays with the kth worst partial relay selection scheme. In our analysis, new expressions for the system's outage probability and the average bit error rate are derived. The effects of the rank of the relay chosen, the average SNR imbalance, and the correlation between the delayed and current signal-to-noise ratio (SNR) on the system performance are investigated. Additionally, simple and accurate outage and average BER approximations are also derived to quantify the performance at high SNR. We also give simulation results to support the theoretical study. View full abstract»

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  • On the Combination of Cooperative Diversity and Multiuser Diversity in Multi-Source Multi-Relay Wireless Networks

    Page(s): 535 - 538
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (194 KB) |  | HTML iconHTML  

    This letter presents an analysis of the combined use of cooperative diversity and multiuser diversity (MUD) in multi-source multi-relay networks. A joint selection scheme, which selects the best source-relay pair to access the channel, is proposed. The main contribution of our work is the derivation of the exact and asymptotic expressions for the outage probability of the system with amplify-and-forward (AF) protocol. From these expressions it is indicated that the total diversity order of M +N can be achieved, where M and N are the number of source nodes and relay nodes, respectively. Based on the outage probability in high signal-to-noise-ratio (SNR) region, the optimum power allocation scheme is also given to improve the system performance. View full abstract»

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  • Blind Unique Identification of MIMO Channels Using Signal Designs and High-Order Moments

    Page(s): 539 - 542
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (276 KB) |  | HTML iconHTML  

    In this letter, a necessary and sufficient condition is developed to check whether a set of polynomial equations is solvable. Furthermore, under the sufficient condition, a closed-form solution is attained using linear Diophantine equation theory. With this, a novel signal design and a row-circular transmission scheme of phase shift keying (PSK) constellations for MIMO flat fading channels are proposed so that the channel coefficients can be uniquely identified. When certain high-order moments of the received signals are available, a closed-form solution to uniquely determine the channel coefficients is given. When only finite received data are available, a numerical algorithm is provided to efficiently and effectively estimate the channel. View full abstract»

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  • Bark Frequency Transform Using an Arbitrary Order Allpass Filter

    Page(s): 543 - 546
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (419 KB) |  | HTML iconHTML  

    We propose an arbitrary order stable allpass filter structure for frequency transformation from Hertz to Bark scale. According to the proposed filter structure, the first order allpass filter is causal, but the second and higher order allpass filters are non-causal. We find that the accuracy of the transformation significantly improves when a second or higher order allpass filter is designed compared to a first order allpass filter. We also find that the RMS error of the transformation monotonically decreases by increasing the order of the allpass filter. View full abstract»

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  • Bit-Error Aware Lossless Compression of Waveform Data

    Page(s): 547 - 550
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (228 KB) |  | HTML iconHTML  

    In this letter, we propose simple bit-error aware lossless compression algorithms for compression and transmission of waveform data in noisy channels. The developed algorithms consist of two stages. The first stage applies linear prediction and the second stage uses the developed residue coder, bi-level block coding or interval entropy coding, in which we show how to choose the optimal coding parameters for compressing the residue sequence from the first stage. We only encode the linear prediction and bi-level block coding or entropy coding parameters using a forward error correction scheme such as (7,4) Hamming codes, leaving residue sequence or residue offset sequence as they are, in order to preserve the performance of compression ratio. Our experiments show that the developed algorithms achieve high compression ratios and the recovered waveforms have a good signal quality when the bit error rate is equal to or less than 0.001. View full abstract»

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  • Spectral Moment Features Augmented by Low Order Cepstral Coefficients for Robust ASR

    Page(s): 551 - 554
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (739 KB) |  | HTML iconHTML  

    We propose a novel Automatic Speech Recognition (ASR) front-end, that consists of the first central Spectral Moment time-frequency distribution Augmented by low order Cepstral coefficients (SMAC). We prove that the first central spectral moment is proportional to the spectral derivative with respect to the filter's central frequency. Consequently, the spectral moment is an estimate of the frequency domain derivative of the speech spectrum. However information related to the entire speech spectrum, such as the energy and the spectral tilt, is not adequately modeled. We propose adding this information with few cepstral coefficients. Furthermore, we use a mel-spaced Gabor filterbank with 70% frequency overlap in order to overcome the sensitivity to pitch harmonics. The novel SMAC front-end was evaluated for the speech recognition task for a variety of recording conditions. The experimental results have shown that SMAC performs at least as well as the standard MFCC front-end in clean conditions, and significantly outperforms MFCCs in noisy conditions. View full abstract»

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  • Statistical-Based Tracking Technique for Linear Structures Detection: Application to Vessel Segmentation in Medical Images

    Page(s): 555 - 558
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB) |  | HTML iconHTML  

    Linear structures such as blood vessels in medical images are important features for computer-aided diagnosis and follow-up of many diseases. In this letter a new tracking-based segmentation method is proposed to detect blood vessels in retinal images. Bayesian segmentation with the Maximum a posteriori (MAP) Probability criterion is used for that purpose. Tests on simulated and retinal images are presented and compared with a vessel detection technique. Our method performs better results. View full abstract»

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  • Distance Estimation With Weighted Least Squares for Mobile Beacon-Based Localization in Wireless Sensor Networks

    Page(s): 559 - 562
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB) |  | HTML iconHTML  

    In large-scale sensor networks, localization with mobile beacons is one of the most efficient ways to deploy sensor nodes as well as locate them. Direct communication with mobile beacons has an advantage of improvement in location accuracy by enabling sensor nodes to measure distances to the mobile beacons. Thus, it is important to improve the accuracy in the distance for high accurate positioning. In this letter, we propose a distance estimation scheme with weighted least squares in mobile beacon-based localization. First, we model distance measurements to a beacon node moving along the given linear tracks. Given our measurement model, the proposed scheme uses weighted least squares to minimize errors in distance measurements. Additionally we analyze the lower bound of errors in our distance estimation based on the Cramer-Rao bound. Simulation results show that our scheme can provide improved accuracy in both distance estimation and position estimation. View full abstract»

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  • Game Theoretic Multimode Precoding Strategy Selection for MIMO Multiple Access Channels

    Page(s): 563 - 566
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (396 KB) |  | HTML iconHTML  

    This paper is concerned with decentralized selection of multimode precoding strategy for multiple-input multiple-output (MIMO) multiple access channels. We formulate it as a discrete noncooperative game. This game is shown to possess at least one pure strategy Nash equilibrium (NE) and the optimal strategy profile which maximizes the sum rate constitutes a pure strategy NE. Then we propose a decentralized algorithm based on learning automata to achieve the NE. A repeated mechanism is introduced to improve the sum rate performance and a mechanism for adapting step size is designed to control the convergence speed. Simulation results show that the proposed algorithm, which only requires limited feedback, can achieve near optimal or optimal sum rate performance. View full abstract»

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  • Efficient Generalized Integer Transform for Reversible Watermarking

    Page(s): 567 - 570
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (341 KB) |  | HTML iconHTML  

    In this letter, an efficient integer transform based reversible watermarking is proposed. We first show that Tian's difference expansion (DE) technique can be reformulated as an integer transform. Then, a generalized integer transform and a payload-dependent location map are constructed to extend the DE technique to the pixel blocks of arbitrary length. Meanwhile, the distortion can be controlled by preferentially selecting embeddable blocks that introduce less distortion. Finally, the superiority of the proposed method is experimental verified by comparing with other existing schemes. View full abstract»

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  • OFDM Transmission for Time-Based Range Estimation

    Page(s): 571 - 574
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (175 KB) |  | HTML iconHTML  

    OFDM is proposed for time-based range estimation (TBRE) and analyzed with respect to its accuracy, both theoretically, in terms of its Cramer-Rao lower bound (CRLB), and practically, in terms of its maximum likelihood estimator (MLE). The CRLB for OFDM transmission is compared to that for pseudo-noise (PN) transmission, demonstrating a large performance gap in favour of OFDM. Moveover, the MLE for TBRE is compared to the commonly used MLE for channel estimation (CE), demonstrating a performance gap in favour of the MLE for TBRE. Finally, the CRLB for OFDM is compared to its corresponding MLE for TBRE, demonstrating a good agreement in performance except for the so-called ??threshold effect??, which is analyzed analytically in this letter. View full abstract»

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  • Including Spatial Correlations in the Statistical MIMO Radar Target Model

    Page(s): 575 - 578
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (510 KB) |  | HTML iconHTML  

    Previous studies of statistical MIMO radar detection performance have used a target model that consists of a large number of point scatterers located within a rectangular target area. These point scatterers have scattering amplitudes that are complex random variables and are spatially uncorrelated, so that the target is a white noise process in space. Spatial correlations are introduced into the target model in this paper, and the impact of these correlations on MIMO radar system detection performance is analyzed. View full abstract»

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  • A Simple Approach to Multiview Face Hallucination

    Page(s): 579 - 582
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1202 KB) |  | HTML iconHTML  

    Most face hallucination methods are usually limited to frontal face with small pose variations. This letter presents a simple and efficient multiview face hallucination (MFH) method to generate high-resolution (HR) multiview faces from a single given low-resolution (LR) one. The problem is addressed in two steps. A simple face transformation method is proposed by defining a constrained least square problem for LR multiview face transformation and a position-patch based face hallucination method is extended to incorporate HR multiview face details. Experimental results show that our approach has some advantages over existing MFH methods. View full abstract»

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  • A DCT Statistics-Based Blind Image Quality Index

    Page(s): 583 - 586
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (535 KB) |  | HTML iconHTML  

    The development of general-purpose no-reference approaches to image quality assessment still lags recent advances in full-reference methods. Additionally, most no-reference or blind approaches are distortion-specific, meaning they assess only a specific type of distortion assumed present in the test image (such as blockiness, blur, or ringing). This limits their application domain. Other approaches rely on training a machine learning algorithm. These methods however, are only as effective as the features used to train their learning machines. Towards ameliorating this we introduce the BLIINDS index (BLind Image Integrity Notator using DCT Statistics) which is a no-reference approach to image quality assessment that does not assume a specific type of distortion of the image. It is based on predicting image quality based on observing the statistics of local discrete cosine transform coefficients, and it requires only minimal training. The method is shown to correlate highly with human perception of quality. View full abstract»

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  • A New Adaptive Switching Median Filter

    Page(s): 587 - 590
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1729 KB) |  | HTML iconHTML  

    A new Adaptive Switching Median (ASWM) filter for removing impulse noise from corrupted images is presented. The originality of ASWM is that no a priori Threshold is needed as in the case of a classical Switching Median filter. Instead, Threshold is computed locally from image pixels intensity values in a sliding window. Results show that ASWM provides better performance in terms of PSNR and MAE than many other median filter variants for random-valued impulse noise. In addition it can preserve more image details in a high noise environment. View full abstract»

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  • Cost-Sensitive Rank Learning From Positive and Unlabeled Data for Visual Saliency Estimation

    Page(s): 591 - 594
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (298 KB) |  | HTML iconHTML  

    This paper presents a cost-sensitive rank learning approach for visual saliency estimation. This approach avoids the explicit selection of positive and negative samples, which is often used by existing learning-based visual saliency estimation approaches. Instead, both the positive and unlabeled data are directly integrated into a rank learning framework in a cost-sensitive manner. Compared with existing approaches, the rank learning framework can take the influences of both the local visual attributes and the pair-wise contexts into account simultaneously. Experimental results show that our algorithm outperforms several state-of-the-art approaches remarkably in visual saliency estimation. View full abstract»

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  • Generalized Sampling Expansion for Bandlimited Signals Associated With the Fractional Fourier Transform

    Page(s): 595 - 598
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (114 KB) |  | HTML iconHTML  

    The aim of the generalized sampling expansion (GSE) is the reconstruction of an unknown continuously defined function f(t), from the samples of the responses of M linear time invariant (LTI) systems, each sampled by the 1/M th Nyquist rate. In this letter, we investigate the GSE in the fractional Fourier transform (FRFT) domain. Firstly, the GSE for fractional bandlimited signals with FRFT is proposed based on new linear fractional systems, which is the generalization of classical generalized Papoulis sampling expansion. Then, by designing fractional Fourier filters, we obtain reconstruction method for sampling from the signal and its derivative based on the derived GSE and the property of FRFT. Last, the potential application of the GSE is presented to show the advantage of the theory. View full abstract»

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  • Temporally Weighted Linear Prediction Features for Tackling Additive Noise in Speaker Verification

    Page(s): 599 - 602
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (387 KB) |  | HTML iconHTML  

    Text-independent speaker verification under additive noise corruption is considered. In the popular mel-frequency cepstral coefficient (MFCC) front-end, the conventional Fourier-based spectrum estimation is substituted with weighted linear predictive methods, which have earlier shown success in noise-robust speech recognition. Two temporally weighted variants of linear predictive modeling are introduced to speaker verification and they are compared to FFT, which is normally used in computing MFCCs, and to conventional linear prediction. The effect of speech enhancement (spectral subtraction) on the system performance with each of the four feature representations is also investigated. Experiments by the authors on the NIST 2002 SRE corpus indicate that the accuracy of the conventional and proposed features are close to each other on clean data. For factory noise at 0 dB SNR level, baseline FFT and the better of the proposed features give EERs of 17.4% and 15.6%, respectively. These accuracies improve to 11.6% and 11.2%, respectively, when spectral subtraction is included as a preprocessing method. The new features hold a promise for noise-robust speaker verification. View full abstract»

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  • Stability Analysis for the Generalized Sidelobe Canceller

    Page(s): 603 - 606
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB) |  | HTML iconHTML  

    One approach for reducing noise from non-target locations in array beamformer applications is to use an adaptive noise cancellation algorithm referred to as the Generalized Sidelobe Canceller (GSC). An analysis is performed to derive a closed-form expression showing the relationship between stability, the number of array channels, adaptive step size ??, and forgetting factor ??. The result is verified by applying the GSC to experimental data with a range of values for ??, ??, and array channels to show when the GSC becomes unstable. View full abstract»

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  • Self-Organizing Maps for Topic Trend Discovery

    Page(s): 607 - 610
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (353 KB) |  | HTML iconHTML  

    The large volume of data on the Internet makes it extremely difficult to extract high-level information, such as recurring or time-varying trends in document content. Dimensionality reduction techniques can be applied to simplify the analysis process but the amount of data is still quite large. If the analysis is restricted to just text documents then Latent Dirichlet Allocation (LDA) can be used to quantify semantic, or topical, groupings in the data set. This paper proposes a method that combines LDA with the visualization capabilities of Self-Organizing Maps to track topic trends over time. By examining the response of a map over time, it is possible to build a detailed picture of how the contents of a dataset change. View full abstract»

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  • Efficient Approach for Sinusoidal Frequency Estimation of Gapped Data

    Page(s): 611 - 614
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (236 KB) |  | HTML iconHTML  

    The problem of frequency estimation for noisy sinusoidal signals from multiple segments or channels, which are referred to as gapped data, is addressed. Based on linear prediction and weighted least squares techniques, an iterative relaxation-based frequency estimator is devised and analyzed. The proposed algorithm is also extended to harmonically related frequencies. Computer simulations are conducted to compare the estimation performance of the developed approach with an existing multichannel frequency estimator and Crame??r-Rao lower bound. View full abstract»

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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.

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Meet Our Editors

Editor-in-Chief
Peter Willett
University of Connecticut
Storrs, CT 06269
peter.willett@uconn.edu