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Signal Processing Letters, IEEE

Issue 12 • Date Dec. 2002

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Displaying Results 1 - 19 of 19
  • Code-constrained blind detection of CDMA signals in multipath channels

    Page(s): 389 - 392
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (379 KB) |  | HTML iconHTML  

    In this letter, a constant-modulus-algorithm-based multiuser detection scheme is proposed for a communication system under multipath propagation. To mitigate channel distortion and multiuser interference, we integrate multiple constraints into the optimization criterion. According to our analysis, the ability of the detector to remove all interference is ensured in the absence of noise when the constraints are properly preselected. However, in the presence of noise, the constraints highly affect the performance of the receiver. In order to optimally combine signals from different paths to achieve performance gains, those constraints can also be treated as variables and jointly optimized with the receiver, as verified by numerical examples. View full abstract»

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  • An AV-based RAKE-like receiver for DS-CDMA systems

    Page(s): 393 - 396
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (291 KB) |  | HTML iconHTML  

    Previously, several detectors based on auxiliary vector (AV) filters were presented to suppress multi-access interference (MAI) in direct-sequence/code-division-multiple-access (DS-CDMA) systems. Knowing the signature waveform of the desired user, these AV-based detectors are a class of promising candidates for MAI suppression due to their superior performance and low computational complexity. However, it is hard to obtain the desired user's signature waveform, which is the convolution of the user's spreading sequence and the channel impulse response, unless the channel vector is known or unless training signals are sent. In this letter, based on both of the merits of AV detectors and RAKE receivers, an AV-based RAKE-like receiver is proposed for DS-CDMA communication systems in multipath channels. Simulation results indicate that the performance of the new receiver is very close to that of the AV detectors, which know the exact signature waveform of the desired user. View full abstract»

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  • A residual echo cancellation scheme for hands-free telephony

    Page(s): 397 - 399
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (383 KB) |  | HTML iconHTML  

    A residual echo cancellation scheme based on the autoregressive (AR) analysis is proposed for hands-free telephony. Residual echo is whitened by the inverse filter using the estimated AR coefficients. Removing the speech characteristics of the residual echo signal, the noise reduction system successfully reduces the power of residual echo as well as that of ambient noise. In a car cabin, the proposed method improved the echo return loss enhancement by 8.7/spl sim/9.9 dB as compared with the conventional combined system. View full abstract»

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  • Binary LUM smoothing

    Page(s): 400 - 403
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (322 KB) |  | HTML iconHTML  

    In this letter, valuable simplification and analysis related to Boolean lower-upper middle (LUM) smoothers are provided. Thus, a class of nonlinear order-statistic LUM smoothers can be implemented as stack filters fast and effectively. An acquisition of the proposed method lies in the simple determination of the binary output according to the configuration of binary samples inside the filter window, where the proposed method takes advantage of the previously developed conversion algorithm between LUM smoothers and positive Boolean functions. Besides the important theoretical aspect, the proposed analysis allows to implement the LUM smoothers in small-area chips that can be successfully used in real image and video applications. View full abstract»

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  • Self-organizing codebooks for trellis-coded VQ

    Page(s): 404 - 406
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (215 KB) |  | HTML iconHTML  

    Because of its computational complexity, vector quantization (VQ) can work only on relatively small vectors, which severely limits its encoding performance. Trellis-coded VQ (TCVQ) circumvents this problem by using VQ in combination with a trellis encoding strategy, thus treating very large blocks of data at once. TCVQ is based on a size-N VQ codebook which is recursively partitioned to form two (possibly nearly optimal) codebooks of size N/2, four of size N/4, etc. Here we show that such a tree of codebooks can be easily designed, without the need of any postprocessing, by means of the Kohonen algorithm. Numerical experiments show the effectiveness of the proposed approach. View full abstract»

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  • Sequential modeling for identifying CpG island locations in human genome

    Page(s): 407 - 409
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (195 KB) |  | HTML iconHTML  

    We consider several sequential processing algorithms for identifying genes in human DNA, based on detecting CpG ("C proceeds G") islands. The algorithms are designed to capture the underlying statistical structure in a DNA sequence. Sequential processing using a Markov model and a hidden Markov model are shown to identify most CpG islands in annotated (marked) DNA subsequences available from publicly available DNA datasets. We also consider a wavelet-based hidden Markov tree (HMT). In the context of the HMT, we address design of adaptive wavelets matched to CpG islands, this accomplished via lifting and genetic-algorithm optimization. View full abstract»

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  • Application of bit-plane decomposition steganography to JPEG2000 encoded images

    Page(s): 410 - 413
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    This letter presents a steganography method based on a JPEG2000 lossy compression scheme and bit-plane complexity segmentation (BPCS) steganography. It overcomes the lack of robustness of bit-plane-based steganography methods with respect to lossy compression of a dummy image: a critical shortcoming that has hampered deployment in a practical scenario. The proposed method is based on a seamless integration of the two schemes without compromising their desirable features and makes feasible the deployment of the merits of a BPCS steganography technique in a practical scenario where images are compressed before being transmitted over the network. Embedding rates of around 15% of the compressed image size were achieved for preembedding 1.0-bpp compressed images with no noticeable degradation in image quality. View full abstract»

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  • Direction estimation of coherent signals using spatial signature

    Page(s): 414 - 417
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (429 KB) |  | HTML iconHTML  

    A computationally efficient spatial signature-based (SS) method is proposed for estimating the directions of arrival of coherent narrowband signals impinging on a uniform linear array. The normalized SS of the coherent signals is blindly estimated from the principal eigenvector of array covariance matrix and then is used to estimate the directions with a modified Kumaresan-Prony method, where a linear prediction model is combined with "subarray" averaging. The proposed method not only has the maximum permissible array aperture and computational simplicity, it also better resolves closely spaced coherent signals with a small length of data and at a lower signal-to-noise ratio. View full abstract»

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  • Multicodebook split vector quantization of LSF parameters

    Page(s): 418 - 421
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB) |  | HTML iconHTML  

    A multicodebook quantization method for improving the performance of the split vector quantization (SVQ) is described. In the proposed method, multiple codebooks having different sizes are trained, and the minimal-size codebook and its codeword satisfying the condition based on the spectral distortion are determined. Several clustering techniques for reducing total bit rate and the analysis of the computational complexity are also presented. Experimental results have shown that the proposed method reduces the number of outliers significantly and achieves a better rate-distortion performance compared with the fixed-bit-rate SVQ, multistage VQ, and variable-bit-rate SVQ. View full abstract»

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  • Context-adaptive smoothing for concatenative speech synthesis

    Page(s): 422 - 425
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB) |  | HTML iconHTML  

    In text-to-speech synthesis, spectral smoothing is often employed to reduce artifacts at unit-joining points. A context-adaptive smoothing method is proposed in this letter, where the amount of smoothing is determined according to context information. Discontinuities at unit boundaries are predicted by a regression tree, and smoothing factors are computed by using predicted discontinuities and real discontinuities at unit boundaries. Experimental results are presented to demonstrate the effectiveness of the proposed method. View full abstract»

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  • Two-dimensional non-Gaussian autoregressive model order determination

    Page(s): 426 - 428
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (260 KB) |  | HTML iconHTML  

    A two-dimensional (2-D) autoregressive (AR) model driven by a non-Gaussian zero-mean independent identically distributed 2-D sequence is considered. The input sequence is not observed. The signal observations may be contaminated by additive Gaussian noise. We consider the problem of model order determination using higher order cumulants of the 2-D signal. We show that the necessary information to determine the 2-D AR model order is implicitly contained in a specific cumulant matrix. The algorithm is based on the computation of three matrix ranks via singular value decomposition. The proposed approach is illustrated via computer simulations. View full abstract»

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  • Block adaptive interference suppression in DS-CDMA systems

    Page(s): 429 - 431
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (298 KB)  

    In this letter, we introduce interference suppression in direct-sequence code-division multiple-access systems using the minimum-mean-square-error criterion based on a block adaptive filtering algorithm. Simulation results show that the proposed implementations of the block algorithm requires much lower computation as compared to recursive least square (RLS) algorithms while maintaining comparable convergence characteristics as that of the RLS algorithm. Also, the block algorithm is shown to be near-far resistant. It is concluded that the proposed implementation is suitable for moderate block sizes, which will have fast convergence while introducing small processing delay. View full abstract»

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  • Adaptive RLS algorithm for blind source separation using a natural gradient

    Page(s): 432 - 435
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB) |  | HTML iconHTML  

    By using the natural gradient on the Stiefel manifold to minimize a nonlinear principle component analysis criterion, this letter proposes a new adaptive recursive-least-squares (RLS) algorithm with prewhitening for blind source separation (BSS), which makes full use of the orthogonality constraint of the separating matrix. Simulations show that the new natural-gradient-based RLS algorithm has faster convergence than the existing least-mean-square algorithms and RLS algorithm for BSS. View full abstract»

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  • Performance of the hierarchical LMS algorithm

    Page(s): 436 - 437
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    Woo (2001) introduced the hierarchical least mean-square (HLMS) adaptive filter algorithm, and demonstrated that it may converge faster than least mean-squares (LMS). This letter reports that the HLMS algorithm may converge to a biased impulse response, not only for colored input (as has previously been shown to be the case for the hierarchical least squares algorithm) but also for white input. We also show that, except in a special case, the penalty for faster convergence is substantially increased misadjustment noise. View full abstract»

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  • Bivariate shrinkage with local variance estimation

    Page(s): 438 - 441
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1310 KB) |  | HTML iconHTML  

    The performance of image-denoising algorithms using wavelet transforms can be improved significantly by taking into account the statistical dependencies among wavelet coefficients as demonstrated by several algorithms presented in the literature. In two earlier papers by the authors, a simple bivariate shrinkage rule is described using a coefficient and its parent. The performance can also be improved using simple models by estimating model parameters in a local neighborhood. This letter presents a locally adaptive denoising algorithm using the bivariate shrinkage function. The algorithm is illustrated using both the orthogonal and dual tree complex wavelet transforms. Some comparisons with the best available results are given in order to illustrate the effectiveness of the proposed algorithm. View full abstract»

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  • Optimized support vector machines for nonstationary signal classification

    Page(s): 442 - 445
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (342 KB) |  | HTML iconHTML  

    This letter describes an efficient method to perform nonstationary signal classification. A support vector machine (SVM) algorithm is introduced and its parameters optimized in a principled way. Simulations demonstrate that our low-complexity method outperforms state-of-the-art nonstationary signal classification techniques. View full abstract»

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  • List of reviewers

    Page(s): 446 - 449
    Save to Project icon | Request Permissions | PDF file iconPDF (148 KB)  
    Freely Available from IEEE
  • Author Index

    Page(s): 450 - 453
    Save to Project icon | Request Permissions | PDF file iconPDF (197 KB)  
    Freely Available from IEEE
  • Subject Index

    Page(s): 453 - 463
    Save to Project icon | Request Permissions | PDF file iconPDF (237 KB)  
    Freely Available from IEEE

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