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Digital Signal Processing, 2007 15th International Conference on

Date 1-4 July 2007

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  • 2007 15th International Conference on Digital Signal Processing

    Publication Year: 2007 , Page(s): i
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  • Copyright page

    Publication Year: 2007 , Page(s): ii
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  • About DSP 2007

    Publication Year: 2007 , Page(s): iii
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  • Welcome Message - Organising Chair

    Publication Year: 2007 , Page(s): iv
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  • Welcome Message - Technical Chair

    Publication Year: 2007 , Page(s): v
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  • Organising Committee

    Publication Year: 2007 , Page(s): vi
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  • International Technical Committee

    Publication Year: 2007 , Page(s): vi
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  • list-reviewer

    Publication Year: 2007 , Page(s): vii - x
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  • Table of contents

    Publication Year: 2007 , Page(s): xi - xxi
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  • [Breaker page]

    Publication Year: 2007 , Page(s): 1
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  • How to Apply ICA on Actual Data ? Example of Mars Hyperspectral Image Analysis

    Publication Year: 2007 , Page(s): 3 - 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5177 KB) |  | HTML iconHTML  

    As any estimation method, results provided by ICA are dependent of a model - usually a linear mixture and separation model - and of a criterion - usually independence. In many actual problems, the model is a coarse approximation of the system physics and independence can be more or less satisfied, and consequently results are not reliable. Moreover, with many actual data, there is a lack of reliable knowledge on the sources to be extracted, and the interpretation of the independent components (IC) must be done very carefully, using partial prior information and with interactive discussions with experts. In this talk, we explain how such a scientific method can take place on the example of analysis of Mars hyperspectral images. View full abstract»

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  • Robust Adaptive Beamforming: When the Worst Case is the Best We Can Do

    Publication Year: 2007 , Page(s): 13
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  • Brain Machine Interfaces: Modeling Strategies for Neural Signal Processing

    Publication Year: 2007 , Page(s): 14
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  • Image Processing: Beyond the Limitation of Human Visual Perception

    Publication Year: 2007 , Page(s): 15
    Cited by:  Papers (1)
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  • From Special Purpose VLSI Architectures to HDTV Processors and Gigabit Wireless Systems

    Publication Year: 2007 , Page(s): 16
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  • [Breaker page]

    Publication Year: 2007 , Page(s): 17
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  • A Class of Adaptively Regularised PNLMS Algorithms

    Publication Year: 2007 , Page(s): 19 - 22
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2472 KB) |  | HTML iconHTML  

    A class of algorithms representing a robust variant of the proportionate normalised least-mean-square (PNLMS) algorithm is proposed. To achieve this, adaptive regularisation is introduced within the PNLMS update, with the analysis conducted for both individual and global regularisation factors. The update of the adaptive regularisation parameter is also made robust, to improve steady state performance and reduce computational complexity. The proposed algorithms are better suited not only for operation in nonstationary environments, but are also less sensitive to changes in the input dynamics and the choice of their parameters. Simulations in a sparse environment show the proposed class of algorithms offer enhanced performance and increased stability over the standard PNLMS. View full abstract»

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  • A Family of Adaptive Algorithms Robust to Impulsive Noise

    Publication Year: 2007 , Page(s): 23 - 26
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2896 KB) |  | HTML iconHTML  

    This paper presents a new approach to the development of a family of adaptive algorithms that are robust to impulsive noise. Unlike other approaches, no cost functions or filtering of the gradient are considered in order to update the filter coefficients. Basically, the algorithm takes into account the distance between the absolute errors and the median of the absolute values of the most recent errors committed by the adaptive filter. The proposed family of algorithms can be considered as a sign-error variant of the LMS algorithm. The proposed adaptive algorithm is successfully tested in terms of accuracy and convergence in a system identification simulation in which an impulsive noise is present. View full abstract»

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  • A Generalised Mixed Norm Stochastic Gradient Algorithm

    Publication Year: 2007 , Page(s): 27 - 30
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (317 KB) |  | HTML iconHTML  

    A novel stochastic gradient algorithm for finite impulse response (FIR) adaptive filters, termed the least sum of exponentials (LSE), is introduced. In order to provide a generalisation of the class of weighted mixed norm algorithms and at the same time avoid problems associated with a large number of free paramaters of such algorithms, LSE is derived by minimising a sum of error exponentials. A rigourous mathematical analysis is provided, resulting in closed form expressions for the optimal weights and the upper bound of the learning rate. The analysis is supported by simulations in a system identification setting. View full abstract»

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  • A Practical Adaptive Blind Multichannel Estimation Algorithm with Application to Acoustic Impulse Responses

    Publication Year: 2007 , Page(s): 31 - 34
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (599 KB) |  | HTML iconHTML  

    We propose a noise robust adaptive blind multichannel identification algorithm for acoustic impulse responses. It has been known that the normalized multichannel frequency domain least-mean-square (NMCFLMS) algorithm misconverges under low signal-to- noise ratio. The coefficients of NMCFLMS converge initially toward the true impulse response after which they then misconverge. The extended NMCFLMS (ext-NMCFLMS) algorithm which has been proposed to mitigate this misconvergence problem assumes the knowledge of magnitude and time-differences-of-arrival (TDOA) of the direct paths for the acoustic impulse responses. In this work, we show how the TDOA can be obtained. More importantly, we present a novel approach to estimate the magnitude of the direct path component under practical conditions. We then show how these estimates can be incorporated to the proposed ext-NMCFLMS with direct path estimation algorithm. We analyze how errors in these estimates affect the performance of the proposed algorithm. View full abstract»

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  • A Unifying Approach to the Derivation of the Class of PNLMS Algorithms

    Publication Year: 2007 , Page(s): 35 - 38
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (393 KB) |  | HTML iconHTML  

    unifying approach to the derivation of the class of proportionate normalised least mean square (PNLMS) algorithms is provided. This is an important class of algorithms where the two most used algorithms are introduced empirically. It is shown that it is possible to derive PNLMS algorithms as a result of an optimisation procedure. This is achieved in a rigorous way, starting from the standard LMS through to the PNLMS with the "sparsification" factor in both the numerator and denominator of the weight update. The proposed approach is generic and also applies to other LMS types of adaptive algorithms. Simulations on benchmark sparse impulse responses support the approach. View full abstract»

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  • Acoustic Echo Cancellation with Reduced-Rank Adaptive Interpolated Filter Based on Parallel-Branch Diversity Decimation

    Publication Year: 2007 , Page(s): 39 - 42
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (466 KB) |  | HTML iconHTML  

    This paper presents an efficient acoustic echo cancellation (AEC) scheme based on reduced-rank interpolated adaptive filtering with parallel decimation, motivated by diversity techniques developed in wireless communications. The proposed scheme jointly optimizes an interpolation filter, a decimator unit and a reduced-rank filter in such a way that the output error is minimized, leading to very substantial improvements of the mean squared error performance. With a practical choice of parameters in AEC, the total computational complexity of the proposed scheme is approximately half of the one of the NLMS algorithm. The numerical examples demonstrate that the proposed algorithm offers very significant reduction in mean squared error performance. View full abstract»

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  • Adaptive Reduced-Rank Filtering using a Projection Operator Based on Joint Iterative Optimization of Adaptive Filters for CDMA Interference Suppression

    Publication Year: 2007 , Page(s): 43 - 46
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (366 KB) |  | HTML iconHTML  

    This paper proposes a novel adaptive reduced-rank filtering scheme based on the joint iterative optimization of adaptive filters. The proposed scheme consists of a joint iterative optimization of a bank of full-rank adaptive filters that constitutes the projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe minimum mean-squared error (MMSE) expressions for the design of the projection matrix and the reduced-rank filter and simple least-mean squares (LMS) adaptive algorithms for its computationally efficient implementation. Simulation results for a CDMA interference suppression application reveals that the proposed scheme significantly outperforms the state-of-the-art reduced- rank schemes, while requiring a significantly lower computational complexity. View full abstract»

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  • An Exact Relaxed Fast Affine Projection Algorithm for Multichannel Active Noise Control

    Publication Year: 2007 , Page(s): 47 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1386 KB) |  | HTML iconHTML  

    In the field of adaptive filtering, affine projection algorithms and their fast implementations are known to produce a good tradeoff between complexity and convergence performance. For multichannel active noise control, some fast affine projection algorithms have consequently been introduced in recent years. However, these previously published algorithms are either based on non-relaxed versions of the fast affine projection algorithm, or on sub-optimal approximations of the algorithm. Non-relaxed versions of the fast affine projection algorithm produce a sub-optimal performance when non-unity step size values are used, which are sometimes desirable in practice. Moreover, not being exact, the previously published algorithms are rather sensitive to the regularization factors being used, making them more difficult to tune and less robust in practice. In this paper, an exact relaxed fast affine projection algorithm for multichannel active noise control is introduced. Simulation results validate the improved convergence of the relaxed algorithm for non-unity step size values, and the good convergence for a much wider range of regularization factors. View full abstract»

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  • Identification of Multi-Reflective Echo Paths using Sub-Rate Adaptive Filtering in Presence of Moderate Aliasing

    Publication Year: 2007 , Page(s): 51 - 54
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (10674 KB) |  | HTML iconHTML  

    Conditions for coexistence of voice and data communication have become complex, and voice aspects of telecommunication, particularly in Voice-over-IP networks, demand echo cancellers to cover all voice channels, as opposed to only long-haul channels, as it used to be in traditional public switched telephone networks. Echo path coverage requirements for the echo cancellers have become more demanding, causing an increase of computational cost of their implementations. One of the methods of decreasing that cost is via implementing sparse echo cancellers. This study explores an approach to additionally reduce computational cost at the stage of pre-processing of input signals for use in a sub-rate adaptive filter, at the expense of aliasing effects. This reduction is based on observations indicating that adaptive filters are not very sensitive to aliasing effects when it comes to detection of multiple reflections. View full abstract»

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