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Signal Processing Letters, IEEE

Issue 4 • Date April 2006

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Displaying Results 1 - 23 of 23
  • Table of contents

    Page(s): c1 - c4
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  • IEEE Signal Processing Letters publication information

    Page(s): c2
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  • Multiple H^\infty Filter-Based Deterministic Sequence Estimation in Non-Gaussian Channels

    Page(s): 185 - 188
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    A novel and more robust implementation is proposed for sequence estimation in uncertain environments with additive non-Gaussian ambient noise and intersymbol interference. This is based on a deterministic performance index that minimizes the effect of worst-case disturbances on the estimation error. The decoder has multiple$H^infty$filters and is in the fashion of per-survivor processing with a Viterbi trellis for decoding. There is a substantial performance improvement over maximum-likelihood sequence estimation, as shown by simulation results obtained for joint channel estimation and symbol decoding in non-Gaussian channels. View full abstract»

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  • A filter coefficient quantization method with genetic algorithm, including simulated annealing

    Page(s): 189 - 192
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB) |  | HTML iconHTML  

    A method based on a genetic algorithm (GA), including a simulated annealing (SA), is proposed for filter coefficient quantization. The proposed method uses the GA to search a population of the quantized filters of a digital filter for the optimal quantized filter. It retains the most accurate frequency characteristic of the original filter, which is either finite impulse response filter or an infinite impulse response filter. The initial population in the GA is generated by binomial distributions, which are not used for the other GAs. An SA is also embedded in the GA search, which can support the GA to converge to the optimum in the early generations. The experimental results verify that our method can provide a quantized filter with a better frequency characteristic than those obtained by the traditional quantization methods, such as rounding off, rounding up, and rounding down. View full abstract»

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  • An efficient algorithm for bandpass sampling of multiple RF signals

    Page(s): 193 - 196
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (280 KB) |  | HTML iconHTML  

    This letter proposes, based on a bandpass sampling theory, a novel method to find available sampling ranges with a low computational complexity and high accuracy for multiple bandpass radio frequency signals. Guard-bands between downconverted signal spectrums are also taken into consideration in determining a minimum sampling frequency. We verify its validity through simulations in terms of the sampling ranges, the minimum sampling frequency, and computational efficiency. View full abstract»

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  • High-resolution image reconstruction from multiple differently exposed images

    Page(s): 197 - 200
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1024 KB) |  | HTML iconHTML  

    Super-resolution reconstruction is the process of reconstructing a high-resolution image from multiple low-resolution images. Most super-resolution reconstruction methods assume that exposure time is fixed for all observations, which is not necessarily true. In reality, cameras have limited dynamic range and nonlinear response to the quantity of light received, and exposure time might be adjusted automatically or manually to capture the desired portion of the scene's dynamic range. In this letter, we propose a Bayesian super-resolution algorithm based on an imaging model that includes camera response function, exposure time, sensor noise, and quantization error in addition to spatial blurring and sampling. View full abstract»

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  • Joint source-channel coding with partially coded index assignment for robust scalable video

    Page(s): 201 - 204
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (168 KB) |  | HTML iconHTML  

    A scalable video coder consisting of motion-compensated temporal filtering coupled with structured vector quantization plus a linear mapping of quantizer indexes that minimizes simultaneously source and channel distortions is presented. The linear index assignment takes the form of either a direct, uncoded mapping or a coded mapping via Reed-Muller codes. Experimental results compare the proposed system to a similar scheme using unstructured vector quantization as well as to a prominent scalable video coder protected by more traditional convolutional codes. The proposed system consistently outperforms the other two schemes by a significant margin for very noisy channel conditions. View full abstract»

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  • Novel quantized DCT for video encoder optimization

    Page(s): 205 - 208
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    A novel technique is proposed to reduce the computational complexity of discrete cosine transform (DCT)-based video encoders. The proposed method merges the DCT and quantization into a single procedure, which is referred to as the novel quantized DCT (NQDCT), such that the DCT output does not need to be explicitly quantized. Thus, a lot of computations related to quantization can be saved. The video encoder's performance using NQDCT is evaluated by comparing it with those using the traditional separate DCT and quantization method and the quantized DCT (QDCT) method. Simulation results demonstrate that the proposed NQDCT outperforms the other two methods in improving the real-time performance for video encoding. View full abstract»

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  • Audio fingerprinting based on normalized spectral subband moments

    Page(s): 209 - 212
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB) |  | HTML iconHTML  

    The performance of a fingerprinting system, which is often measured in terms of reliability and robustness, is directly related to the features that the system uses. In this letter, we present a new audio-fingerprinting method based on the normalized spectral subband moments. A threshold used to reliably determine a fingerprint match is obtained by modeling the features as a stationary process. The robustness of the normalized moments was evaluated experimentally and compared with that of the spectral flatness measure. Among the considered subband features, the first-order normalized moment showed the best performance for fingerprinting. View full abstract»

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  • Security analysis of transformed-key asymmetric watermarking system

    Page(s): 213 - 215
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (94 KB) |  | HTML iconHTML  

    Asymmetric watermarking schemes have been widely discussed recently. Transformed-key asymmetric watermarking (TKAW) system is one of the schemes, which was proposed by Choi et al. This letter discusses the weaknesses of TKAW. In TKAW, the inner product of the received signal and public key almost equals to zero. As a result, it cannot resist projection attack. To prove this point, we will demonstrate how to find the most relevant unwatermarked signal y˜ for a given watermark embedded signal y and prove that ||y-y||≤|α|, where α is a constant adjusted to a value that makes the watermark imperceptible. Moreover, we also find that the feature y-y˜, a predicted watermark of a stego image, can be copied from a stego image to another image, which means that the TKAW system cannot resist copy attack either. View full abstract»

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  • Image feature-based space-time processing for ground moving target detection

    Page(s): 216 - 219
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (896 KB) |  | HTML iconHTML  

    An image feature-based space time processing (IFSTP) algorithm is introduced to effectively detect ground moving targets in clutter and jamming via airborne radar. This new approach exploits the distinct image features of targets and interference signals in the angle-Doppler domain. An image segmentation algorithm, referred to as region growing, extracts targets and interference features in the angle-Doppler domain, and an innovative block-size detection algorithm discriminates between moving targets and interference based on the extracted image features. The proposed IFSTP algorithm is particularly suitable for detecting ground moving targets in highly nonhomogeneous clutter environments, without any requirement for clutter covariance estimation. View full abstract»

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  • Active differential CMOS imaging device for human face recognition

    Page(s): 220 - 223
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (424 KB) |  | HTML iconHTML  

    This letter describes an original CMOS imaging system dedicated to human face recognition. The main interest of this work is to provide ambient light invariant images and facilitate segmentation of the face from the background. This system has been implemented in a specially designed CMOS smart image sensor with only one analog memory per pixel. This simple pixel design gives the possibility to incorporate this functionality into classic low-cost CMOS image sensors. One of its possible applications is face recognition, since the human face appearance is dramatically dependent on illumination conditions. A first indoor experience with different illumination conditions shows that a simple correlation-based verification algorithm on face images of 25 people of the INT database gives promising results. View full abstract»

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  • Adaptive filtering algorithms designed using control Liapunov functions

    Page(s): 224 - 227
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB)  

    The standard conjugate gradient (CG) method uses orthogonality of the residues to simplify the formulas for the parameters necessary for convergence. In adaptive filtering, the sample-by-sample update of the correlation matrix and the cross-correlation vector causes a loss of the residue orthogonality in a modified online algorithm, which, in turn, results in loss of convergence and an increase of the filter quadratic mean error. This letter extends a recently proposed control Liapunov function analysis of the CG method viewed as a dynamic system in the standard feedback configuration to the case of adaptive filtering. View full abstract»

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  • Time-domain fast fixed-point algorithms for convolutive ICA

    Page(s): 228 - 231
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB) |  | HTML iconHTML  

    This letter presents new blind separation methods for moving average (MA) convolutive mixtures of independent MA processes. They consist of time-domain extensions of the FastICA algorithms developed by Hyvarinen and Oja for instantaneous mixtures. They perform a convolutive sphering in order to use parameter-free fast fixed-point algorithms associated with kurtotic or negentropic non-Gaussianity criteria for estimating the source innovation processes. We prove the relevance of this approach by mapping the mixtures into linear instantaneous ones. Test results are presented for artificial colored signals and speech signals. View full abstract»

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  • Wavelet deconvolution in a periodic setting using cross-validation

    Page(s): 232 - 235
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    The wavelet deconvolution method WaveD using band-limited wavelets offers both theoretical and computational advantages over traditional compactly supported wavelets. The translation-invariant WaveD with a fast algorithm improves further. The twofold cross-validation method for choosing the threshold parameter and the finest resolution level in WaveD is introduced. The algorithm's performance is compared with the fixed constant tuning and the default tuning in WaveD. View full abstract»

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  • Prediction of inverse covariance matrix (PICM) sequences for STAP

    Page(s): 236 - 239
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    In this letter, we study issues associated with applying least-squares estimation to predict the inverse covariance matrix in bistatic airborne radar systems. For the bistatic ground moving target indication radar, the clutter Doppler frequency depends on the range for all array geometries. This range dependency leads to problems in clutter suppression through space-time adaptive processing (STAP) techniques. This paper proposes a new method of obtaining an estimate of the inverse covariance matrix using linear prediction techniques. Simulation results show a significant improvement in processor performance as compared to conventional STAP methods. View full abstract»

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  • CFAR detection of extended and multiple point-like targets without assignment of secondary data

    Page(s): 240 - 243
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB) |  | HTML iconHTML  

    We design and assess adaptive schemes to detect extended and multiple point-like targets embedded in correlated Gaussian noise. Proposed algorithms rely on either the generalized likelihood ratio test (GLRT) or ad hoc procedures. Such detectors make it possible to get rid of distinct secondary data and guarantee the constant false alarm rate (CFAR) property with respect to the covariance matrix of the disturbance. A preliminary performance assessment, conducted by resorting to simulated data, also in comparison to the so-called modified GLRT (MGLRT) proposed in , has shown that newly introduced CFAR detectors may represent a viable means to deal with uncertain scenarios. View full abstract»

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  • Split-order linear prediction for segmentation and harmonic spectral modeling

    Page(s): 244 - 247
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB)  

    Linear prediction (LP) analysis, split in two stages, is proposed for a combined time-frequency analysis. The first-stage LP is used to obtain the residual signal and extract each one of its cycles, whose harmonic spectrum is then modeled by the second-stage estimate from discrete all-pole algorithms. Thus, harmonic cycle spectra are modeled with less than 1 dB in log spectral distortion (SD). Further, a method is proposed to approximate the log SD target. A linear approximation to the log power spectral ratio in the log SD gradient is shown to provide better model fit to harmonic cycle spectra. View full abstract»

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  • IEEE Signal Processing Letters Information for authors

    Page(s): 248 - 249
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  • Special issue on blind signal processing for speech and audio applications

    Page(s): 250
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  • Special issue on content storage and delivery in peer-to-peer network

    Page(s): 251
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  • Special issue on semantic image and video indexing in broad domains

    Page(s): 252
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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