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Signal Processing Letters, IEEE

Issue 1 • Date Jan. 2004

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Displaying Results 1 - 23 of 23
  • Table of contents

    Page(s): 01
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  • IEEE Signal Processing Letters Society Information

    Page(s): 0_2
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  • Blind multiuser detection by kurtosis maximization/minimization

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (136 KB)  

    Blind multiuser detection is studied in the presence of multipath distortion. The kurtosis of the receiver's output is minimized with respect to the receiver's parameters subject to multiple linear constraints. The constraints are dependent on the spreading codes of the user of interest. In order to combine multipath signals optimally, the kurtosis is parameterized by the constraint vector as well and is further maximized. It is shown that under some conditions, the optimal constraint vector converges to the channel vector of the desired user irrespective of noise, and the proposed receiver ensures perfect cancellation of both intersymbol interference and multiuser interference. Meanwhile, a minimum mean-square-error receiver can be constructed from the constraint vector. View full abstract»

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  • Joint design of channel-optimized multistage vector quantizer

    Page(s): 5 - 7
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    A novel channel-optimized multistage vector quantization (COMSVQ) codec is presented in which the stage codebooks are jointly designed. The proposed codec uses a signal source and channel-dependent distortion measure to encode line spectral frequencies derived from segments of a speech signal. Simulation results are provided to demonstrate the consistent reduction in the spectral distortion obtained using the proposed codec as compared to the conventional sequentially designed channel-matched multistage vector quantizer. View full abstract»

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  • Frames and sampling theorems for translation-invariant subspaces

    Page(s): 8 - 11
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    A sampling theorem for frames in translation-invariant subspaces of L2(R) is established, which is a generalization of a result of W. Chen and S. Itoh for Riesz bases (see IEEE Trans. Sig. Processing, vol.46, p.2822-4, 1998). Then, some necessary conditions for sampling are derived for Riesz bases. Some relationships and properties are also derived about the relevant functions. View full abstract»

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  • A matching-pursuit/GSIC-based algorithm for DS-CDMA sparse-channel estimation

    Page(s): 12 - 15
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    A sparse-channel estimation algorithm for multiuser environments is developed with application to time-of-arrival (TOA)-based radiolocation. To eliminate multiple-access interference (MAI), the generalized successive interference cancellation (GSIC) algorithm is used. At each GSIC stage, the matching-pursuit (MP) or least squares (LS) methods are used to estimate the sparse channel. The GSIC/MP and GSIC/LS are compared via simulations, and the GSIC/MP performs better than the GSIC/LS. View full abstract»

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  • Fingerprint enhancement in the singular point area

    Page(s): 16 - 19
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    Minutiae extraction is one of the most important steps for automatic fingerprint identification systems. However, the performance of minutiae extraction relies heavily on an enhancement algorithm. There are many enhancement algorithms that depend on the local orientation field of the fingerprint. In the singular point area, because the local orientation changes very rapidly, enhancement is not accurate, so that the result is very bad. We present a new method and design a new filter to enhance a fingerprint in the singular point area. We distinguish the singular point area first. Then we design a new filter to enhance this area. Experimental results show a significant improvement of fingerprint enhancement in the singular point area, and the time required for our algorithm is reduced. View full abstract»

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  • Nonasymptotic statistical performance of beamforming for deterministic signals

    Page(s): 20 - 22
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    The purpose of this letter is to investigate, in the deterministic case, the nonasymptotic behavior of beamforming estimation of the direction of arrival of a single source impinging on a uniform linear array. We derive an approximate analytical expression of the maximum-likelihood mean-squared error that is valid for all SNR ranges and number of snapshots. Computer simulations confirm the validity of the theoretical investigations. View full abstract»

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  • Nonasymptotic performance analysis of beamforming with stochastic signals

    Page(s): 23 - 25
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    This letter is devoted to the analysis of the nonasymptotic behavior of beamforming for the bearing estimation of a single stochastic source impinging on an uniform linear array. An analytic expression of the maximum-likelihood mean-squared error is derived. This general expression is valid at any SNR and for any number of snapshots. Simulation results verify the analytically predicted performances. View full abstract»

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  • A robust algorithm for linearly constrained adaptive beamforming

    Page(s): 26 - 29
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (176 KB)  

    A new approach to robust adaptive beamforming for wideband array signals is proposed. General steering vector errors, such as direction-of-arrival mismatch and array positional error, are modeled by "time-delay errors" and compensated for by self-adjusted interpolation filtering. The proposed method effectively overcomes the target-signal cancellation problem without suffering from loss in the degree of freedom for interference rejection, as verified by simulations. View full abstract»

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  • A subspace tracking algorithm using the fast Fourier transform

    Page(s): 30 - 32
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    E.C. Real et al. have presented an algorithm for fast tracking of a signal subspace or interference subspace for application in adaptive detection or estimation (see ICASSP '97; IEEE Trans. Sig. Processing, vol.47, p.1036-45, 1999). For cases in which the signal matrix is formed from a single-channel discrete-time signal, we show how one can further reduce computation in the fast approximate subspace tracking (FAST) algorithm by using the fast Fourier transform. View full abstract»

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  • Temporal decomposition based on a rate-distortion criterion

    Page(s): 33 - 35
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    This letter addresses a temporal decomposition (TD) technique that is based on a rate-distortion criterion. In the proposed TD scheme, a set of interpolation functions is constructed from a given training corpus, and the optimum target points are found in the sense of minimizing, not only spectral distortion, but also bit rates. The results of the simulation show that an average spectral distortion of about 1.4 dB can be achieved at an average bit rate of about 8 bits/frame. View full abstract»

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  • Proposal of a speech detector based on eigenspectra

    Page(s): 36 - 39
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    This letter deals with the problem of speech detection in the context of hands-free telecommunications. The principle of the detectors studied is based on the coherence function (ordinary or partial coherence), which is usually computed from the periodogram (first approach). The present work is aimed at proposing a new approach to compute the coherence from the eigenspectra with a view to reduce the bias. A statistical analysis is carried out to estimate the bias of both coherence estimators. Both approaches are compared experimentally, and results show the superiority of the new estimator. View full abstract»

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  • Discriminative training for concatenative speech synthesis

    Page(s): 40 - 43
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    In this letter, we propose an approach to train the cost functions used for unit selection in concatenative speech synthesis. We first view the unit selection as a classification problem, and we apply the discriminative training technique, which is found to be an efficient way to perform parameter estimation in speech recognition. Instead of defining an objective function that accounts for the subjective speech quality, we take the classification error as the objective function to be optimized. The classification error is approximated by a smooth function, and the relevant parameters are updated by means of the gradient descent technique. View full abstract»

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  • A hybrid subband adaptive system for speech enhancement in diffuse noise fields

    Page(s): 44 - 47
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    Performance of adaptive noise cancellation (ANC) degrades severely when uncorrelated noise components are present at the two inputs. Thus, practical background diffuse noises pose a serious problem for ANC systems. In this letter, we propose a new hybrid system that integrates subband adaptive filters (SAFs) and a Wiener filter. The hybrid system is implemented on an oversampled DFT filterbank that efficiently integrates the SAF and the Wiener filter components in the frequency-domain. Performance evaluation of the hybrid system in presence of diffuse noise interference shows that the proposed system is superior to both the Wiener filter and the SAF subsystems. View full abstract»

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  • Differential of the mutual information

    Page(s): 48 - 51
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    In this letter, we compute the variation of the mutual information, resulting from a small variation in its argument. Although the result can be applied in many problems, we consider only one example: the result is used for deriving a new method for blind source separation in linear mixtures. The experimental results emphasize the performance of the resulting algorithm. View full abstract»

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  • Elliptic-cylindrical wavelets: the Mathieu wavelets

    Page(s): 52 - 55
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    This note introduces a new family of wavelets and a multiresolution analysis that exploits the relationship between analyzing filters and Floquet's solution of Mathieu differential equations. The transfer function of both the detail and the smoothing filter is related to the solution of a Mathieu equation of the odd characteristic exponent. The number of notches of these filters can be easily designed. Wavelets derived by this method have potential application in the fields of optics and electromagnetism. View full abstract»

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  • A normalized robust mixed-norm adaptive algorithm for system identification

    Page(s): 56 - 59
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    A normalized robust mixed-norm (NRMN) algorithm for system identification in the presence of impulsive noise is introduced. The standard robust mixed-norm (RMN) algorithm exhibits slow convergence, requires a stationary operating environment, and employs a constant step-size that needs to be determined a priori. To overcome these limitations, the proposed NRMN algorithm introduces a time-varying learning rate and, thus, no longer requires a stationary environment, a major drawback of the RMN algorithm. The proposed NRMN exhibits increased convergence rate and substantially reduces the steady-state coefficient error, as compared to the least mean square (LMS), normalized LMS (NLMS), least absolute deviation (LAD), and RMN algorithm. View full abstract»

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  • IEEE Signal Processing Letters Information for authors

    Page(s): 60 - 61
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  • IEEE Transactions on Speech and Audio Processing Special Issue on Data Mining of Speech, Audio and Dialog

    Page(s): 62
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  • IEEE copyright form

    Page(s): 63 - 64
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  • IEEE Signal Processing Society Information

    Page(s): 0_3
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  • Blank page [back cover]

    Page(s): 04
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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