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Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468)

25-25 Aug. 1999

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  • Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468)

    Publication Year: 1999
    Request permission for commercial reuse | PDF file iconPDF (218 KB)
    Freely Available from IEEE
  • Author index

    Publication Year: 1999, Page(s):565 - 566
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    Freely Available from IEEE
  • Multi-channel piecewise selective averaging of cognitive evoked potentials with variable latency

    Publication Year: 1999, Page(s):459 - 467
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (520 KB)

    This work is about the development of an alternative way of averaging evoked potentials (EP) of cognitive activities. Since the main assumption of invariant waveforms time locked to the eliciting events does not hold for cognitive EPs, averaging results in distorted estimates. The authors' alternative selective averaging finds similar subsequences of fixed length with variable latency which are co... View full abstract»

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  • Subspace techniques in speech enhancement

    Publication Year: 1999, Page(s):449 - 458
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (456 KB)

    This paper concerns speech enhancement. Speech is first modelled and then model parameters used to design a Kalman smoother to reduce the background noise. The 4SID (subspace state space system identification), DOA (direction-of-arrival) and polynomial techniques are described within a common subspace state space framework, and assumptions for each technique stated. It is shown that 4SID methods m... View full abstract»

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  • Rate-constrained self-organizing neural maps and efficient psychovisual methods for low bit rate video coding

    Publication Year: 1999, Page(s):390 - 399
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (452 KB)

    The video coding problem is essentially an operational distortion-rate issue where the underlying input pixel data, probability distributions and dimensions are discrete, unknown and not smooth. In the low bit rate case the high resolution assumptions for vector quantization are not strictly valid and the problem is exacerbated. However, by considering the rate-constrained operational points on se... View full abstract»

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  • Pattern classification using a mixture of factor analyzers

    Publication Year: 1999, Page(s):525 - 534
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (396 KB)

    This paper describes a practical application of a mixture of factor analyzers (MFA) to pattern recognition. The MFA extracts locally linear manifolds underlying given high dimensional data. In this respect, the NFA-based approach is similar to the conventional subspace methods that approximate the data space with low dimensional linear subspaces. However, the MFA-based classifier, unlike the conve... View full abstract»

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  • A comparison among feature selection methods based on trained networks

    Publication Year: 1999, Page(s):205 - 214
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB)

    We present a review of feature selection methods, based on the analysis of a trained multilayer feedforward network, which have been applied to neural networks. Furthermore, a methodology that allows evaluating and comparing feature selection methods is carefully described. This methodology is applied to the 19 reviewed methods in a total of 15 different real world classification problems. We pres... View full abstract»

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  • Robust machine fault detection with independent component analysis and support vector data description

    Publication Year: 1999, Page(s):67 - 76
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (428 KB)

    We propose an approach to fault detection in rotating mechanical machines: fusion of multichannel measurements of machine vibration using independent component analysis (ICA), followed by a description of the admissible domain (part of the feature space indicative of normal machine operation) with a support vector domain description (SVDD) method. The SVDD method enables the determination of an ar... View full abstract»

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  • Approximation by random networks with bounded number of layers

    Publication Year: 1999, Page(s):166 - 175
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (396 KB)

    This paper discusses the function approximation properties of the Gelenbe random neural network (GNN). We use an extension of the basic model: the bipolar GNN (BGNN). We limit the networks to being feedforward and consider the case where the number of hidden layers does not exceed the number of input layers. We show that the feedforward BGNN with s hidden layers (total of s+2 layers) can uniformly... View full abstract»

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  • Model combination and weight selection criteria for speaker verification

    Publication Year: 1999, Page(s):439 - 448
    Cited by:  Papers (1)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (428 KB)

    We focus on the score combination for three separate modeling approaches as applied to text-dependent speaker verification. The modeling methods that are evaluated consist of the neural tree network (NTN), hidden Markov model (HMM), and dynamic time warping (DTW). One of the main challenges in combining scores of several models is how to select the weight for each model. One method is to use equal... View full abstract»

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  • Maximum likelihood blind source separation in Gaussian noise

    Publication Year: 1999, Page(s):343 - 352
    Cited by:  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (396 KB)

    This paper presents a new maximum likelihood (ML) approach to the separation of convolutive mixtures of unobserved sources in the presence of additive temporally white Gaussian noise (ATWGN). The proposed method proceeds in two steps. First, the ML estimate of the mixing system is computed and, afterwards, this estimate is employed to obtain the ML estimates of the sources. The proposed algorithms... View full abstract»

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  • Discrimination of cylinders with different wall thicknesses using neural networks and simulated dolphin sonar signals

    Publication Year: 1999, Page(s):477 - 486
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (500 KB)

    This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness difference experiment and demonstrates high accuracy for small wall thickness differences. Results from the ex... View full abstract»

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  • Gradient based adaptive regularization

    Publication Year: 1999, Page(s):87 - 94
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (288 KB)

    A technique to optimize regularization parameters for a given supervised training problem is presented. A training database is applied to minimize a regularized cost function, and a validation database is used to estimate and optimize generalization properties by means of a modification of regularization. The performance is validated for a vowel classification task and compared to other approaches View full abstract»

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  • Applications of SOAR to monochromatic image restoration

    Publication Year: 1999, Page(s):363 - 369
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (320 KB)

    This study proposes a novel autoassociator for associative storage of gray scale images. An autoassociator is a system capable of completing an incomplete pattern, when it is presented as part of a learned pattern. Patterns in the proposed associative architecture are gray scale images with integer values. The proposed system, based on a previously developed technique called “SOAR”, is... View full abstract»

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  • Hierarchy of probabilistic principal component subspaces for data mining

    Publication Year: 1999, Page(s):497 - 506
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (612 KB)

    Visual exploration has proven to be a powerful tool for multivariate data mining. Most visualization algorithms aim to find a projection from the data space down to a visually perceivable rendering space. To reveal all of the interesting aspects of complex data sets living in a high-dimensional space, a hierarchical visualization algorithm is introduced which allows the complete data set to be vis... View full abstract»

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  • Margin-like quantities and generalized approximate cross validation for support vector machines

    Publication Year: 1999, Page(s):12 - 20
    Cited by:  Papers (4)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (304 KB)

    We examine support vector machines (SVM) from the point of view of solutions to variational problems in a reproducing kernel Hilbert space. We discuss the generalized comparative Kullback-Leibler distance as a target for choosing tuning parameters in SVMs, and we propose that the generalized approximate cross validation estimate of them is a reasonable proxy for this target. We indicate an interes... View full abstract»

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  • Learning Gestalt of surfaces in natural scenes

    Publication Year: 1999, Page(s):380 - 389
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (520 KB)

    We develop a computational model for scenes with surfaces that have rough and non-smooth small-scale structure but with a perceived global (larger-scale) geometric form. Examples include grass and meadow, surfaces textured with sand-paper, natural scenes having rough texture such as the skin of crocodile, pine cones, a field of sea urchins, forests, ripples and waves on water surfaces, etc. Anothe... View full abstract»

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  • Adaptive Web caching using logistic regression

    Publication Year: 1999, Page(s):515 - 524
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (468 KB)

    A fundamental understanding of Web access patterns is necessary before we can tackle cache performance issues. Due to the extremely dynamic nature of the Web, any techniques we employ must be able to adapt to changing conditions on the Web. We introduce a near-optimal cache algorithm, based on complete a priori knowledge of future Web access. In reality, such knowledge is unavailable. To enable us... View full abstract»

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  • Sequential support vector machines

    Publication Year: 1999, Page(s):31 - 40
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (420 KB)

    We derive an algorithm to train support vector machines sequentially. The algorithm makes use of the Kalman filter and is optimal in a minimum variance framework. It extends the support vector machine paradigm to applications involving real-time and non-stationary signal processing. It also provides a computationally efficient alternative to the problem of quadratic optimisation View full abstract»

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  • A control theory formulation for random variate generation

    Publication Year: 1999, Page(s):132 - 138
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (264 KB)

    The need to simulate complex systems in a Monte Carlo manner necessitates efficient methods for generating random variates. We propose a method for random variate generation. The method is based on a control theory formulation. We use a cascade structure consisting of a neural network “controller” and a density estimator (“plant”). The neural network “controller&rdquo... View full abstract»

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  • A stable and robust ICA algorithm based on t-distribution and generalized Gaussian distribution models

    Publication Year: 1999, Page(s):283 - 292
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (376 KB)

    We propose a novel independent component analysis (ICA) algorithm which enables one to separate mixtures of sub-Gaussian, super-Gaussian and Gaussian primary source signals. Alternative activation functions in the algorithm are derived by using parameterized t-distribution and generalized Gaussian distribution density models. The functions are self-adaptive based on estimating the high-order momen... View full abstract»

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  • On condition monitoring of exhaust valves in marine diesel engines

    Publication Year: 1999, Page(s):554 - 563
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (524 KB)

    The feasibility of noninvasive characterisation of exhaust valve conditions in large marine diesel engines were experimentally investigated on a four cylinder 500 mm bore 2-stroke marine diesel engine at MAN B&W Diesel's Research Center in Copenhagen, Denmark. The experiments comprised three different valve conditions, where two were concerned with artificially induced valve burn-through situa... View full abstract»

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  • Hidden Markov mixtures of experts for prediction of non-stationary dynamics

    Publication Year: 1999, Page(s):195 - 204
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (468 KB)

    The prediction of non-stationary dynamical systems may be performed by identifying appropriate sub-dynamics and an early detection of mode changes. We present a framework which unifies the mixtures of experts approach and a generalized hidden Markov model with an input-dependent transition matrix: the hidden Markov mixtures of experts (HMME). The gating procedure incorporates state memory, informa... View full abstract»

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  • General statistical inference by an approximate application of the maximum entropy principle

    Publication Year: 1999, Page(s):112 - 121
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (492 KB)

    We propose a learning method for building a general statistical inference engine, operating on discrete feature spaces. Such a model allows inference on any feature given values for the other features (or for a feature subset). Bayesian networks (BNs) are versatile tools that possess this inference capability. However, while the BN's explicit representation of conditional independencies is informa... View full abstract»

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  • A Gaussianity measure for blind source separation insensitive to the sign of kurtosis

    Publication Year: 1999, Page(s):58 - 66
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (332 KB)

    Various existing criteria to characterize the statistical independence are applied in blind source separation and independent component analysis. However, almost all of them are based on parametric models. The distribution model mismatch between the output PDF (probability density functions) and the chosen underlying distribution model is a serious problem in blind signal processing. Nonparametric... View full abstract»

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