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Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop

Date 11-13 Dec. 2000

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  • Neural Networks for Signal Processing X [front matter]

    Publication Year: 2000, Page(s):i - iv
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    Freely Available from IEEE
  • Index

    Publication Year: 2000, Page(s):945 - 947
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    Freely Available from IEEE
  • Lateral inhibition mechanism in computational auditory model and its application in robust speech recognition

    Publication Year: 2000, Page(s):785 - 794 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (580 KB)

    In the auditory neural system, the lateral inhibition mechanism is very common, such as in the cochlear nucleus, auditory cortex, etc. The function of this lateral inhibition is to sharpen the contrast of the temporal and spatial structures, thus prominent features of stimulation in spatial and temporal domains can be enhanced. In this paper, a new mathematical model based on lateral inhibition is... View full abstract»

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  • Support vector machines for speaker verification and identification

    Publication Year: 2000, Page(s):775 - 784 vol.2
    Cited by:  Papers (50)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (460 KB)

    The performance of the support vector machine (SVM) on a speaker verification task is assessed. Since speaker verification requires binary decisions, support vector machines seem to be a promising candidate to perform the task. A new technique for normalising the polynomial kernel is developed and used to achieve performance comparable to other classifiers on the YOHO database. We also present res... View full abstract»

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  • Implementation of channel repacking algorithms on Hopfield neural networks in cellular systems

    Publication Year: 2000, Page(s):765 - 774 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (396 KB)

    Channel repacking, the rearrangement of channels once a subscriber leaves a cellular mobile communication system, is one of many ways of increasing the capacity of the system. A channel repacking algorithm is proposed and implemented on a Hopfield neural network. Results based on simulations from two different cellular systems indicate that there is an improvement in capacity when channel repackin... View full abstract»

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  • Fingerprint image compression

    Publication Year: 2000, Page(s):517 - 526 vol.2
    Cited by:  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (420 KB)

    Storage of fingerprint image databases needs allocation of huge secondary storage devices. To reduce the increasing demand on storage space, efficient data compression techniques are badly needed. In addition to that, the exchange of fingerprint images between governmental agencies could be done fast. The compression algorithm must also preserve the original information in the original image. This... View full abstract»

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  • Networks for networks: Internet analysis using graphical statistical models

    Publication Year: 2000, Page(s):755 - 764 vol.2
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (452 KB)

    A novel graphical framework for statistical modeling of distributed computer networks is presented in this paper. The framework enables the inference of packet losses across internal links in the network based solely on external (end-to-end) measurements, which can be easily made at end systems without network cooperation. This inference problem is commonly referred to as network tomography. Our m... View full abstract»

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  • Echocardiographic image sequence segmentation using self-organizing maps

    Publication Year: 2000, Page(s):594 - 603 vol.2
    Cited by:  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (528 KB)

    Presents a new approach for echocardiographic image sequence segmentation. The proposed method uses a self-organizing map to approximate the probability density function of the image patterns. The map is post-processed by the k-means clustering algorithm, in order to detect groups of neurons whose weights are similar. Each segmented image of the sequence is generated by correlation of its pixels a... View full abstract»

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  • Using statistical and neural network methods to explore the relationship between systematic risk and firm's long term investment activities

    Publication Year: 2000, Page(s):851 - 858 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (328 KB)

    The paper presents a neural network method to explore the relationship between the systematic risk and long term investing activities for Taiwan's companies in the fiber industry and electronics industry. In general, diversification from long-term investment may reduce a firm's systematic risk, but the empirical results in some literature are controversial. For years regression methods have been u... View full abstract»

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  • Face detection and eye localization by neural network based color segmentation

    Publication Year: 2000, Page(s):507 - 516 vol.2
    Cited by:  Papers (3)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (632 KB)

    This paper presents a neural network based scheme for human face detection and eye localization in color images under an unconstrained scene. A self-growing probabilistic decision-based neural network (SPDNN) is used to learn the conditional distribution for each color classes. Pixels of a color image are first classified into facial or non-facial regions, then pixels in the facial region are foll... View full abstract»

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  • Multiuser demodulators using adaptive polynomial perceptrons in CDMA systems

    Publication Year: 2000, Page(s):746 - 754 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (328 KB)

    The polynomial perceptron multiuser demodulator (PPMUD) and the bilinear recursive polynomial perceptron multiuser demodulator with decision feedback (BRPMUD) are applied to a digital communication system using spread spectrum. The proposed multiuser demodulators are compared with the conventional receiver, the multilayer perceptron multiuser demodulator (MLPMUD) and the radial basis function mult... View full abstract»

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  • Face recognition using a new distance metric

    Publication Year: 2000, Page(s):584 - 593 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (468 KB)

    Many classification techniques use a distance metric as a measure of the similarity between patterns, and their generalisation performance is often strongly related to the effectiveness of the measure. This paper introduces a distance metric based on the Mahalanobis distance function, which is statistically more reliable than some metrics but does not discard discriminating information, often rega... View full abstract»

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  • Optimal feature selection using information maximisation: case of biomedical data

    Publication Year: 2000, Page(s):841 - 850 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (360 KB)

    The hybrid information maximisation (HIM) algorithm is derived. This algorithm is based on maximising the mutual information (MI) between the input and output of a network using the infomax principle, and between outputs of different network modules using the Imax algorithm. These two folds enable reducing the redundancy in output units in addition to selecting higher order features from input uni... View full abstract»

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  • A neural predictor for blind equalization of digital communication systems: is it plausible?

    Publication Year: 2000, Page(s):736 - 745 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB)

    In digital channel equalization, self-learning techniques are used in the cases where a training period is not available. Considering the transmitted sequence as composed of independent random variables, the equalization task can be done by means of prediction. In this work we propose artificial neural networks (ANN), instead of a linear prediction device, in order to obtain a better performance a... View full abstract»

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  • Measuring the complexity of the ocean floor

    Publication Year: 2000, Page(s):576 - 583 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (472 KB)

    In an attempt to classify the complexity of the ocean floor, we suggest a neural network-based algorithm which predicts a pixel based on its surroundings. The mean square of the difference between the original sidescan sonar image and the predicted image is then used as a measure of the complexity of the image View full abstract»

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  • Automatic evaluation of adaptive algorithms over the Internet

    Publication Year: 2000, Page(s):886 - 895 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (716 KB)

    We describe a system for the automatic evaluation of adaptive algorithms over the Internet. We motivate our discussion by setting up a system to evaluate region of interest finding algorithms. This is a signal processing/pattern recognition problem that occurs in many different application domains, and for which neural network solutions have been proposed as highly flexible and trainable solutions... View full abstract»

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  • Use of neural networks for feature based recognition of liver region on CT images

    Publication Year: 2000, Page(s):831 - 840 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (472 KB)

    Medical diagnostic support systems are gaining popularity due to easy access of computers in this field and the increasing workload of radiologists. The automatic processing of X-ray images, segregation of different regions, and detection of certain features are a few of the objectives of this task. Neural networks have been successfully applied to various pattern recognition problems. High-resolu... View full abstract»

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  • Neural-network-based real-time human body posture estimation

    Publication Year: 2000, Page(s):477 - 486 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (476 KB)

    This paper proposes a real-time human body posture estimation method using ANNs. The network is composed of three ANNs and a decision logic unit. The ANNs' input is the result of a function analysis on a human silhouette's contour extracted from camera images and the ANNs' output indicates the feature points' positions on the contour. The decision logic unit synthesizes each of the ANNs' output ve... View full abstract»

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  • Low-complexity fusion of intensity, motion, texture, and edge for image sequence segmentation: a neural network approach

    Publication Year: 2000, Page(s):497 - 506 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (572 KB)

    We develop an image sequence segmentation scheme which uses intensity, motion, edge, and texture features. The proposed scheme is simple and inherently parallel in nature. Motion confidence values are employed for a feature weighting scheme in order to suppress unreliable feature components. These feature vectors are quantized by training self-organizing feature maps (SOFM). In order to generate m... View full abstract»

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  • Adaptive multidimensional spline neural network for digital equalization

    Publication Year: 2000, Page(s):729 - 735 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (268 KB)

    Presents a new neural architecture that is suitable for digital signal processing applications. The architecture, which is based on adaptable multidimensional activation functions, allows one to collect information from the previous network layer in aggregate form. In other words, the number of network connections (the structural complexity) can be very low with respect to the problem complexity. ... View full abstract»

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  • A novel method for CFAR data fusion

    Publication Year: 2000, Page(s):711 - 720 vol.2
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (484 KB)

    Detection systems with distributed sensors and data fusion are increasingly being used by surveillance systems. There has been a great deal of theoretical study into decentralized detection networks that are composed of similar independent sensors. To solve the resulting nonlinear system, an exhaustive search and some approximation methods are usually adopted. However, these often either cause the... View full abstract»

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  • A recursive approach to joint image restoration and compensated blur identification

    Publication Year: 2000, Page(s):567 - 575 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (380 KB)

    Presents a new recursive scheme to blind image deconvolution based on joint image restoration and compensated blur identification. The technique projects a novel cost function into the image and blur subspaces, and optimizes them recursively using alternating minimization. A hierarchical neural network is employed to provide an adaptive, perception-based restoration. The sparse connections of the ... View full abstract»

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  • A Hopfield neural network approach for the reconstruction of wide-bandwidth sonar data

    Publication Year: 2000, Page(s):876 - 885 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (536 KB)

    Sonar systems with small physical apertures are easier to mount on small vessels and remotely operated vehicles (ROVs). Such systems however are limited in terms of angular resolution. Although wide-bandwidth signals may be used to increase the range resolution of a sonar system, angular resolution is unaffected. Such limitations can be overcome if the region of interest in the underwater environm... View full abstract»

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  • Nonlinear active noise control using Lyapunov theory and RBF network

    Publication Year: 2000, Page(s):916 - 925 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (416 KB)

    A new approach to design an efficient algorithm for the ANC system is proposed. The transversal filter-based controllers (FIR and IIR) are first considered. A Lyapunov function of the error is defined and filter coefficients are then adaptively adjusted based on Lyapunov stability theory so that the error converges to zero asymptotically. The design is independent of the statistical properties of ... View full abstract»

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  • Agglomerative learning for general fuzzy min-max neural network

    Publication Year: 2000, Page(s):692 - 701 vol.2
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (448 KB)

    Proposes an agglomerative learning algorithm based on similarity measures defined for hyperbox fuzzy sets. It is presented in a context of clustering and classification problems that are tackled using a general fuzzy min-max (GFMM) neural network. The agglomerative scheme's robust behaviour in the presence of noise and outliers and its insensitivity to the order of the training pattern presentatio... View full abstract»

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