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Signal Processing Letters, IEEE

Issue 10 • Date Oct. 2005

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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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  • Optimal time segmentation for overlap-add systems with variable amount of window overlap

    Page(s): 665 - 668
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB) |  | HTML iconHTML  

    In this letter, we propose a new best basis search algorithm for computing the optimal time segmentation of a signal, given a predefined cost measure. The new algorithm solves a problem that arises when the individual signal segments are windowed and overlap-add is applied between adjacent signal segments. When windows having a variable tail shape are employed, the minimization of a cost measure is faced with dependencies between segmental costs due to varying window overlap. A dynamic programming-based algorithm is presented that takes into account these dependencies. It computes both the optimal split positions and the optimal amount of window overlap at these split positions in polynomial time. The proposed algorithm gives an upper bound to the achievable performance of existing algorithms. Experimental results for a modified discrete cosine transform-based processing system are presented, both for entropy and rate-distortion cost measures. These results show a performance gain over existing schemes at the cost of an increased computational complexity. View full abstract»

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  • On performance of sphere decoding and Markov chain Monte Carlo detection methods

    Page(s): 669 - 672
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (168 KB) |  | HTML iconHTML  

    In a recent work, it has been found that the suboptimum detectors that are based on Markov chain Monte Carlo (MCMC) simulation techniques perform significantly better than their sphere decoding (SD) counterparts. In this letter, we explore the sources of this difference and show that a modification to existing sphere decoders can result in some improvement in their performance, even though they still fall short when compared with the MCMC detector. We also present a novel SD detector that is an exact realization of max-log-MAP detector. We call this exact max-log SD detector. Comparison of the results of this detector with those of the max-log version of the MCMC detector reveals that the latter is near optimal. View full abstract»

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  • Blind adaptive multiuser detection based on affine projection algorithm

    Page(s): 673 - 676
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB) |  | HTML iconHTML  

    In this letter, we introduce a novel blind multiuser detector based on the affine projection algorithm (APA) for direct-sequence code-division multiple-access (DS-CDMA) systems. Computational complexities of least mean-squares (LMS), recursive least squares (RLS), Kalman, and APA-based blind multiuser detection algorithms are compared. The proposed technique has similar convergence and tracking properties as the RLS algorithm with much reduced computational cost. Simulation results are presented to compare our APA-based algorithm with the blind LMS, RLS, and Kalman schemes. View full abstract»

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  • Optimal correlating transform for erasure channels

    Page(s): 677 - 680
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    In this letter, we derive a gradient-based algorithm for computing the optimal transform when coefficients are transmitted over an erasure channel whose statistics are known. The discrete transform introduces correlation among the coefficients with consequent performance improvement against losses. Simulations show appreciable improvements over standard schemes and also good robustness when loss probabilities are only roughly estimated. View full abstract»

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  • Image denoising algorithm via doubly local Wiener filtering with directional windows in wavelet domain

    Page(s): 681 - 684
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    Local Wiener filtering in the wavelet domain is an effective image denoising method of low complexity. In this letter, we propose a doubly local Wiener filtering algorithm, where the elliptic directional windows are used for different oriented subbands in order to estimate the signal variances of noisy wavelet coefficients, and the two procedures of local Wiener filtering are performed on the noisy image. The experimental results show that the proposed algorithm improves the denoising performance significantly. View full abstract»

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  • A novel objective no-reference metric for digital video quality assessment

    Page(s): 685 - 688
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (160 KB) |  | HTML iconHTML  

    A novel objective no-reference metric is proposed for video quality assessment of digitally coded videos containing natural scenes. Taking account of the temporal dependency between adjacent images of the videos and characteristics of the human visual system, the spatial distortion of an image is predicted using the differences between the corresponding translational regions of high spatial complexity in two adjacent images, which are weighted according to temporal activities of the video. The overall video quality is measured by pooling the spatial distortions of all images in the video. Experiments using reconstructed video sequences indicate that the objective scores obtained by the proposed metric agree well with the subjective assessment scores. View full abstract»

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  • Statistical voice activity detection using a multiple observation likelihood ratio test

    Page(s): 689 - 692
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB) |  | HTML iconHTML  

    Currently, there are technology barriers inhibiting speech processing systems that work in extremely noisy conditions from meeting the demands of modern applications. This letter presents a new voice activity detector (VAD) for improving speech detection robustness in noisy environments and the performance of speech recognition systems. The algorithm defines an optimum likelihood ratio test (LRT) involving multiple and independent observations. The so-defined decision rule reports significant improvements in speech/nonspeech discrimination accuracy over existing VAD methods that are defined on a single observation and need empirically tuned hangover mechanisms. The algorithm has an inherent delay that, for several applications, including robust speech recognition, does not represent a serious implementation obstacle. An analysis of the overlap between the distributions of the decision variable shows the improved robustness of the proposed approach by means of a clear reduction of the classification error as the number of observations is increased. The proposed strategy is also compared to different VAD methods, including the G.729, AMR, and AFE standards, as well as recently reported algorithms showing a sustained advantage in speech/nonspeech detection accuracy and speech recognition performance. View full abstract»

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  • Fast decomposition of filterbanks for the state-of-the-art audio coding

    Page(s): 693 - 696
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    This letter derives fast decomposition for the quadrature mirror filterbanks (QMFs) of the low power spectral band replication (SBR) tools in the MPEG high efficiency advanced audio coding (HE AAC) decoder. In contrast with the standard method where computation-intensive matrix operations are employed in the QMF, the proposed method decomposes the matrix operations into conventional discrete cosine transform of type II and III (DCT-II and DCT-III) and simple permutations for easy implementation. The computational complexity can be also reduced effectively by using fast algorithms for DCT. View full abstract»

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  • Synthesis filters design for coding gain in oversampled filter banks

    Page(s): 697 - 700
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (224 KB) |  | HTML iconHTML  

    In this letter, we study the impact of the design freedom brought about by oversampling in perfect reconstruction oversampled filter banks, on the choice of synthesis filters that maximize the coding gain. In particular, based on the expression of the coding gain for the oversampled case, we show the dependency of the coding gain on both analysis and synthesis filters. We explore how the choice of synthesis filters can affect the coding gain, given a fixed set of analysis filters. We show that the para-pseudo-inverse is a good choice for the maximization of the coding gain when the corresponding analysis filters have been optimized for coding gain under critical sampling. View full abstract»

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  • A fast algorithm for bidimensional EMD

    Page(s): 701 - 704
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB) |  | HTML iconHTML  

    In this letter, we describe a new method for bidimensional empirical mode decomposition (EMD). This decomposition is based on Delaunay triangulation and on piecewise cubic polynomial interpolation. Particular attention is devoted to boundary conditions that are crucial for the feasibility of the bidimensional EMD. The study of the behavior of the decomposition on a different kind of image shows its efficiency in terms of computational cost, and the decomposition of Gaussian white noises leads to bidimensional selective filter banks. View full abstract»

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  • A new chirp scaling algorithm based on the fractional Fourier transform

    Page(s): 705 - 708
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB) |  | HTML iconHTML  

    The fractional Fourier transform (FrFT), which is a generalized form of the well-known Fourier transform, has only recently started to appear in the field of signal processing. This has opened up the possibility of a new range of potentially promising and useful applications. In this letter, we develop a new FrFT-based chirp scaling algorithm (CSA) and compare its performance with the classical CSA based on the fast Fourier transform (FFT). Simulation results show that the FrFT-based CSA can offer significantly enhanced features compared to the classical FFT-based approach. View full abstract»

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  • DOA estimation via a network of dumb sensors under the SENMA paradigm

    Page(s): 709 - 712
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB) |  | HTML iconHTML  

    Following the SENMA concept, we consider a wireless network of very dumb and cheap sensors, polled by a travelling "rover". Sensors are randomly placed and isotropic: Individually, they have no ability to resolve the direction of arrival (DOA) of an acoustic wave. However, they do observe the wavefront at different times. We assume that the communication load must be as limited as possible, so that these times cannot be communicated to the rover. Notwithstanding the lack of transmission of arrival times and the lack of DOA resolution ability of the individual sensors, DOA estimation is possible and simple, and asymptotic efficiency becomes closely approximated after a reasonable number of rover snapshots. Key features are the directionality of the rover antenna, the area it surveys, and the average number of sensors inside that area, as accorded a Poisson distribution. View full abstract»

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  • Phase-mode versus delay-and-sum spherical microphone array processing

    Page(s): 713 - 716
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    Phase-mode spherical microphone array processing, also known as spherical harmonic array processing, has been recently studied for various applications. The spherical array configuration provides desired three-dimensional symmetry, while the phase modes provide frequency-independent spatial processing. This letter employs the spherical harmonic framework to compare the well-known delay-and-sum to the phase-mode processing for spherical arrays. The two approaches show similar performance at frequencies where the upper spherical harmonic order equals the product of the wave number and sphere radius. However, at lower frequencies, phase-mode processing maintains the same directivity, limited by signal-to-noise ratio, while for delay-and-sum, spatial resolution deteriorates. View full abstract»

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  • On source association of DOA estimation under multipath propagation

    Page(s): 717 - 720
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (168 KB) |  | HTML iconHTML  

    For direction of arrival (DOA) estimation under a multipath environment, algorithms exist to estimate the DOAs of all paths associated with different sources, by employing various schemes to cope with coherent signals induced by multipath. Most of these methods do not provide any information on which source a detected path belongs to, i.e., source association. However, information on source association is useful for identifying, locating, and tracking the sources. In this letter, we propose a novel method to associate all paths to each source based on the assumption that the DOAs of all paths have been detected by an existing method. The description of our source association algorithm and the simulation are based on wideband cyclostationary signals. However, our algorithm can be easily modified to work for both stationary signals and narrowband cyclostationary signals. View full abstract»

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  • Artifact removal from electroencephalograms using a hybrid BSS-SVM algorithm

    Page(s): 721 - 724
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB) |  | HTML iconHTML  

    Artifacts such as eye blinks and heart rhythm (ECG) cause the main interfering signals within electroencephalogram (EEG) measurements. Therefore, we propose a method for artifact removal based on exploitation of certain carefully chosen statistical features of independent components extracted from the EEGs, by fusing support vector machines (SVMs) and blind source separation (BSS). We use the second-order blind identification (SOBI) algorithm to separate the EEG into statistically independent sources and SVMs to identify the artifact components and thereby to remove such signals. The remaining independent components are remixed to reproduce the artifact-free EEGs. Objective and subjective assessment of the simulation results shows that the algorithm is successful in mitigating the interference within EEGs. View full abstract»

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  • Blind channel estimation using zero-lag slice of third-order moment

    Page(s): 725 - 727
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (144 KB) |  | HTML iconHTML  

    An iterative algorithm is presented for blind channel estimation of a nonminimum phase system using the zero-lag slice (ZS) of its third-order moment (TOM) only. The proposed method has simple computations because it is performed by using simple one-dimensional (1-D) operations with fast convergency and needs calculation of the ZS only. Furthermore, our method achieves good results since the ZS estimate obtained from the received signal exhibits high reliability. Simulations verify the good performance of our method in relatively lower signal-to-noise ratios (SNRs) and when there is a channel length mismatch. View full abstract»

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  • IEEE Signal Processing Letters Information for authors

    Page(s): 728 - 729
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  • International Conference on Image Processing (ICIP 2006)

    Page(s): 730
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    Freely Available from IEEE
  • IEEE Odyssey 2006: The Speaker and Language Recognition Workshop

    Page(s): 731
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  • IEEE Signal Processing Society 2006 International Workshop on Multimedia Signal Processing

    Page(s): 732
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    Freely Available from IEEE
  • 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