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International Joint Conference on Neural Networks (IJCNN)

作者： J. Salazar M. Robinson M.R. Azimi-Sadjadi Signal/Image Processing Laboratory Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA

A classification scheme is developed for classifying underwater mine-like and non-mine-like objects from acoustic backscattered signals. This scheme uses a predictive network along with a neural network classifier. Th... 详细信息

关键词： Pattern classification Underwater acoustics Fusion power generation signal processing Neural networks Acoustic signal detection Probability computer errors Laboratories Acoustical engineering

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Accurate estimation of the signal baseline in DNA chromatograms

Accurate estimation of the signal baseline in DNA chromatogr...

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IEEE Workshop on Neural Networks for signal processing

作者： L. Andrade E.S. Manolakos Communications and Digital Signal Processing (CDSP) Center for Research and Graduate Studies Electrical and Computer Engineering Department Northeastern University Boston MA USA

Estimating accurately the varying baseline level in different parts of a DNA chromatogram is a challenging and important problem for accurate base-calling. We are formulating the problem in a statistical learning framework and propose an Expectation-Maximization algorithm for its solution. In addition we also present a faster, iterative histogram based method for estimating the background of the signal in small size windows. The two methods can be combined with regression techniques to correct the baseline in all regions of the chromatogram and are shown to work well even in areas of low SNR. By improving the separation of clusters, baseline correction actions reduce the classification errors when using the BEM base-caller developed in our group.

关键词： Statistical learning Bayesian methods signal resolution signal to noise ratio Data mining Digital signal processing DNA computing Expectation-maximization algorithms Iterative methods Histograms

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Thresholding video images for text detection

Thresholding video images for text detection

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Du, Eliza Yingzi Chang, Chein-I Thouin, Paul D. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Department of Defense Fort MeadeMD20755 United States

ISBN: (纸本)0769516963

Thresholdging video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding methods that work well for document images may not work effectively for video images in some applications. This paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. In order to demonstrate its performance a comparative study is conducted among the proposed thresholding method and several thresholding techniques which are widely used for document and gray scale images. The experimental results show that thresholdging video images is far more difficult than thresholding document images and simple histogrambased methods generally do not perform well. © 2002 IEEE.

关键词： Pattern recognition

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Unsupervised Kalman filter approach to signature estimation for remotely sensed imagery

Unsupervised Kalman filter approach to signature estimation ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jianwei Wang Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA

ISBN: (纸本)078037536X

The commonly used linear spectral unmixing is generally performed on a single pixel basis and does not take advantage of inter-pixel spatial correlation. The Kalman filter has been considered to extend the linear unmixing by taking into account both spectral and spatial correlation. In addition to a linear mixture model implemented as a measurement equation, it includes a state equation to keep track of changes in between pixels. However, Kalman filtering requires the complete knowledge of image endmembers present in image data, which is generally not available and very difficult to obtain a priori. In order to relax this dilemma, this paper presents an unsupervised Kalman filtering (UKF) approach to signature estimation for remotely sensed images. It first uses an anomaly detector combined with orthogonal subspace projection (OSP) to extract desired image endmember signatures directly from the image data, then further applies a discrimination measure to classify the extracted signatures into a set of distinct signatures that will be used in the measurement equation. In order for the UKF to effectively capture spatial correlation among sample image pixels, the state equation is also implemented dynamically to adjust the state transition matrix adaptively. Experimental results have shown that the proposed UKF approach provides additional advantages over the commonly used spectral-based linear unmixing methods.

关键词： Pixel Equations Kalman filters Filtering Nonlinear filters Data mining Remote sensing Detectors signal processing Image processing

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Digital envelope detector for blood pressure measurement using an oscillometric method

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Journal of Medical engineering and Technology 2002年第3期26卷 117-122页

作者： Lee, J.Y. Kim, J.K. Yoon, G. Samsung Advanced Institute of Technology Yong-In Korea Republic of Digital Signal Processing Laboratory Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of

Blood pressure measurement in the finger artery offers some advantages compared with that in the brachial artery. However, volume oscillometric signals obtained from finger artery measurement are often influenced by motion artefact due to respiration, speaking, involuntary or voluntary movement, etc. In this paper, we developed a digital envelope detector to detect the maximum oscillation criterion in blood pressure measurement for the first time. The digital envelope detector is robust to noise signals generated by motion artefact and filters out the carrier frequency efficiently. To verify the feasibility of our method, we measured blood pressure for eight subjects using our developed system. The results were compared with the auscultation method. In the case of using a digital envelope detector, we could reduce the mean difference error and standard deviation by 30-40%. Our proposed digital envelope detector is a useful tool to improve the accuracy of blood pressure measurement in finger artery.

关键词： Biomedical engineering

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Automatic thresholding abundance fractional images for mixed pixel classification

Automatic thresholding abundance fractional images for mixed...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Shao-Shan Chiang Chein-I Chang Department of Electrical Engineering Lunghwa University of Science and Technology Taoyuan Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA

Mixed pixel classification is different from spatial-based image classification in the sense that the former deals with abundance fractional images resulting from mixed pixels as opposed to classification maps produced by the latter. As a result, mixed pixel classification is generally carried out by visual inspection on the generated abundance fractional images. Consequently, it can be very subjective and vary with different human interpretations. Under such circumstance, it is difficult to substantiate an algorithm and conducting a comparative analysis is impossible. This paper presents one histogram-based approach to thresholding abundance fractional images. It thresholds an abundance fractional image into a binary image using a probability of confidence as a threshold value.

关键词： Pixel Humans Image analysis Inspection Image segmentation signal processing Image processing Laboratories computer science Image classification

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Step-response-based characterization of nonuniform perfect-reconstruction filter banks

Step-response-based characterization of nonuniform perfect-r...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： S. Samadi A. Nishihara M.O. Ahmad M.N.S. Swamy Center for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada The Center for Research and Development of Educational Technology Tokyo Institute of Technology Tokyo Japan

An algebraic characterization of nonuniform perfect-reconstruction (PR) filter banks with integer decimation factors is derived. The PR property is formulated in the z domain based on the response of the systems to delayed unit step signals. This leads to derivation of a new class of characterizing formulas in terms of the rate conversion factors and the transfer functions of channel filters. We use the formulas to give a set of analytic necessary and sufficient conditions for a nonuniform delay chain filter bank to be a PR system. These conditions are identical to those that characterize exact covering systems of congruence relations using roots of unity. We introduce important results from the mathematics literature on exact covering systems. These results elucidate the admissible factors of decimation in nonuniform PR delay chain systems with maximally distinct decimation factors.

关键词： Channel bank filters Filter bank Delay systems Educational technology Sufficient conditions signal processing Research and development Transfer functions Books Wavelet transforms

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Relative entropy-based methods for image thresholding

Relative entropy-based methods for image thresholding

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Jianwei Wang Eliza Yingzi Du Chein-I Chang P.D. Thouin Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore USA Department of Defense Fort Meade USA

A relative entropic thresholding approach was recently developed by Chang et al. (see Pattern Recognition, vol. 27, no. 9, p. 1275-1289, 1994). This paper extends Chang et al.'s approach to two more relative entropy-based thresholding methods, called local relative entropy thresholding (LRE) and joint relative entropy thresholding (JRE). Since relative entropy based methods are sensitive to sparse image histograms, a histogram compression and translation is suggested to compact the histogram. In order to achieve an objective assessment, uniformity and shape measures are introduced for performance evaluation. Experimental results show that when image histograms are sparse, with the proposed histogram compression and translation, JRE and LRE generally perform better than Chang et al.'s approach.

关键词： Entropy Histograms Shape measurement Image coding Remote sensing signal processing Image processing computer science Hardware Inspection

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A nonlinear lowpass filter that eliminates peak attenuation

A nonlinear lowpass filter that eliminates peak attenuation

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： James McNames Brahm Goldstein Biomedical Signal Processing Laboratory Electrical and Computer Engineering Portland State University Portland OR USA Complex Systems Laboratory Department of Pediatrics Oregon Health and Sciences University Portland OR USA

Linear-phase lowpass filters are often used as a preprocessing step in signal processing applications to eliminate high frequency components of noise that do not overlap with the signal spectrum. signals with sharp peaks confound this type of noise reduction because sharp peaks have a broad spectrum and are significantly attenuated by lowpass filters. This paper describes a simple method that restores the signal peaks to their full amplitude by adding a filtered estimate of the peak residuals to the original lowpass filter output. Examples are given of the nonlinear filter applied to a Poisson process, an electrocardiogram, and an extracellular microelectrode recording of neuron action potentials.

关键词： Filtering algorithms Estimation Neurosurgery Attenuation Surges Noise Filtering

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A model-following adaptive controller using radial basis function networks

A model-following adaptive controller using radial basis fun...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： T. Ibayashi T. Hoya Y. Ishida Department of Electronics and Communications Meiji University Kawasaki Japan Laboratory for Advanced Brain Signal Processing Brain Science Institute Wakoh Japan Department of Electrical and Electronic Engineering Meiji University Kawasaki Japan

In this paper, we propose a method to design a model-following adaptive controller using radial basis function networks (RBF-NNs). The method is very simple to implement by exploiting the properties of RBF-NNs. The proposed method identifies linear or nonlinear plants and implements a stable model-following adaptive controller by utilizing identification results. Simulation results show the effectiveness of the proposed control schemes.

关键词： Programmable control Adaptive control Radial basis function networks Control systems Vectors Design methodology Biological neural networks Neural networks Neurons Equations

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