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Circuit design and exponential stabilization of memristive neural networks

Neural networks : the official journal of the International Neural Network Society 2015年 63卷 48-56页

作者： Shiping Wen Tingwen Huang Zhigang Zeng Yiran Chen Peng Li Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: wenshiping226@***. Texas A & M University at Qatar Doha 5825 Qatar. Electronic address: tingwen.huang@qatar.tamu.edu. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: zgzeng527@***. Electrical and Computer Engineering Department University of Pittsburgh Pittsburgh PA 15261 USA. Electronic address: yic52@pitt.edu. Department of Electrical and Computer Engineering Texas A & M University College Station TX 77843 USA. Electronic address: pli@tamu.edu.

This paper addresses the problem of circuit design and global exponential stabilization of memristive neural networks with time-varying delays and general activation functions. Based on the Lyapunov-Krasovskii functional method and free weighting matrix technique, a delay-dependent criteria for the global exponential stability and stabilization of memristive neural networks are derived in form of linear matrix inequalities (LMIs). Two numerical examples are elaborated to illustrate the characteristics of the results. It is noteworthy that the traditional assumptions on the boundness of the derivative of the time-varying delays are removed.

关键词： Memristor Neural networks Stabilization

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MULTI-SPECTRAL DOCUMENT image BINARIZATION USING image FUSION AND BACKGROUND SUBTRACTION TECHNIQUES

MULTI-SPECTRAL DOCUMENT IMAGE BINARIZATION USING IMAGE FUSIO...

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IEEE International Conference on image processing

作者： Nikolaos Mitianoudis Nikolaos Papamarkos Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace

ISBN: (纸本)9781479957521

In this paper, the authors exploit a multispectral image representation to perform more accurate document image binarisation compared to previous color representations. In the first stage, image fusion is employed to create a "document" and a "background" image. In the second stage, the FastICA algorithm is used to perform background subtraction. In the third stage, a spatial kernel K-harmonic means classifier binarizes the FastICA output. The proposed system outperforms previous efforts on document image binarization.

关键词： Document image Binarization image Fusion Multi-spectral imaging Independent Component Analysis

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2D-PCA shape models: Application to 3D reconstruction of the human teeth from a single image

2D-PCA shape models: Application to 3D reconstruction of the...

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3rd International MICCAI Workshop on Medical computer Vision, MCV 2013

作者： Abdelrehim, Aly S. Farag, Aly A. Shalaby, Ahmed M. El-Melegy, Moumen T. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9783319055299

Accurate modeling of human teeth is mandatory for many reasons. Some of them are (1) Providing comfort to patients during mold process, and (2) Enhancing the accuracy level for oral orthodontist and dental care personnel. Shape from Shading (SFS) proved to be of great help in this problem, considering the fact that human tooth surface is textureless. In this paper, we address the problem of 3D tooth reconstruction, and improve the current algorithms. The approached developed in this paper reconstructs the teeth from single image shading with 2D-PCA shape priors that have more sophisticated reflectance model. Oren-Nayar-Wolff model was used for modeling the surface reflectance. This formulation uses shape priors as got from a set of training CT scans of real human teeth. Our experiments show promising quantitative results, which builds the infrastructure for having an optical based approach that accounts for inexpensive and radiationless human tooth reconstruction. © 2014 Springer International Publishing Switzerland.

关键词： computerized tomography

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Recursive Automatic Target Generation Process for Unsupervised Hyperspectral Target Detection

Recursive Automatic Target Generation Process for Unsupervis...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Cheng Gao Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland

ISBN: (纸本)9781479953141

Automatic target generation process (ATGP) has been found very useful and effective for unsupervised target detection. It performs a sequence of orthogonal subspace projection to extract potential targets of interest. One major issue arises in ATGP is how to terminate the algorithm in the sense that how many targets are required for ATGP to generate before it is terminated. This paper presents a recursive version of ATGP, referred to as recursive ATGP (RATGP) which has two advantages. One is no need of inverting any matrix as ATGP does for finding each target. Most importantly, a stopping rule can be derived for ATGP via RATGP is also developed using the Neyman-Pearosn detection theory to determine how many targets needed to be generated by RATGP before it is terminated.

关键词： Automatic target generation process (ATGP) Recursive ATGP (RATGP)

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Evolutionary membrane computing: A comprehensive survey and new results

Evolutionary membrane computing: A comprehensive survey and ...

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作者： Zhang, Gexiang Gheorghe, Marian Pan, Linqiang Pérez-Jiménez, Mario J. School of Electrical Engineering Southwest Jiaotong University Chengdu 610031 China Department of Computer Science University of Sheffield Regent Court Portobello Street Sheffield S1 4DP United Kingdom Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n Sevilla 41012 Spain

Evolutionary membrane computing is an important research direction of membrane computing that aims to explore the complex interactions between membrane computing and evolutionary computation. These disciplines are receiving increasing attention. In this paper, an overview of the evolutionary membrane computing state-of-the-art and new results on two established topics in well defined scopes (membrane-inspired evolutionary algorithms and automated design of membrane computing models) are presented. We survey their theoretical developments and applications, sketch the differences between them, and compare the advantages and limitations. © 2014 Elsevier Inc. All rights reserved.

关键词： Surveys

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Dynamic PET denoising incorporating a composite image guided filter

Dynamic PET denoising incorporating a composite image guided...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Lijun Lu Debin Hu Xiaomian Ma Jianhua Ma Arman Rahmim Wufan Chen Guangdong Provincial Key Laboratory of Medical Image Processing Southern Medical University Guangzhou Guangdong China Department of Radiology and Department of Electrical & Computer Engineering Johns Hopkins University Baltimore MD USA

We proposed a composite image guided filtering technique for dynamic PET denoising to enable quantitatively enhanced time frames. The guided filter computes the filtering output by considering the content of a guidance image, which can be the input image itself or a different image. In this paper, the composite image from the entire time series is considered as the guidance image. Thus, a local linear model is established between the composite image and individual PET time frames. Subsequently, linear ridge regression is exploited to derive an explicit composite image guided filter. For validation, 20 minute FDG PET data from a NEMA NU 4-2008 IQ phantom were acquired in the list-mode format via the Siemens Invoen micro PET, and were subsequently divided and reconstructed into 20 frames. We compared the performances (including visual and quantitative profiles) of the proposed composite image guide filter (CIGF) with a classic Gaussian filter (GF), and a highly constrained back projection (HYPR) filter. The experimental results demonstrated the proposed filter to achieve superior visual and quantitative performance without sacrificing spatial resolution. The proposed CIGF is considerably effective and has great potential to process the data with high noise for dynamic PET scans.

关键词： Positron emission tomography image reconstruction Filtering Noise reduction Phantoms

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IMART software for correction of motion artifacts in images collected in intravital microscopy

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Intravital 2014年第1期3卷 e28210页

作者： Kenneth W Dunn Kevin S Lorenz Paul Salama Edward J Delp Division of Nephrology School of Medicine Indiana University Indianapolis IN USA. Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA. Department of Electrical and Computer Engineering

Intravital microscopy is a uniquely powerful tool, providing the ability to characterize cell and organ physiology in the natural context of the intact, living animal. With the recent development of high-resolution microscopy techniques such as confocal and multiphoton microscopy, intravital microscopy can now characterize structures at subcellular resolution and capture events at sub-second temporal resolution. However, realizing the potential for high resolution requires remarkable stability in the tissue. Whereas the rigid structure of the skull facilitates high-resolution imaging of the brain, organs of the viscera are free to move with respiration and heartbeat, requiring additional apparatus for immobilization. In our experience, these methods are variably effective, so that many studies are compromised by residual motion artifacts. Here we demonstrate the use of IMART, a software tool for removing motion artifacts from intravital microscopy images collected in time series or in three dimensions.

关键词： fluorescence microscopy image analysis image processing image registration in vivo imaging intravital microscopy motion artifact multiphoton microscopy

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Relationship exploration among PPI, ATGP and VCA via theoretical analysis

Relationship exploration among PPI, ATGP and VCA via theoret...

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作者： Chang, Chein-I. Wen, Chia-Hsien Wu, Chao-Cheng Department of Computer Science and Electrical Engineering Remote Sensing Signal and Image Processing Laboratory University of Maryland 1000 Hilltop Circle Baltimore MD 21250 United States Department of Computer Science and Information Engineering Providence University Taichung Taiwan Department of Computer Science and Information Management Providence University 200 Taiwan Boulevard Shalu Dist. Taichung City 43301 Taiwan Department of Electrical Engineering National Taipei University of Technology 1 Zhongxiao E. Rd. Taipei 106 Taiwan

The principle of orthogonality using orthogonal projection (OP) is the key concept to develop mean squared error estimation theory in signal processing and communications. It has also found its way in a wide variety of applications in hyperspectral imaging. This paper explores close relationships among three OP-based algorithms, pixel purity index (PPI), vertex component analysis (VCA) in endmember extraction, automatic target generation process (ATGP) in mixed pixel classification and target detection, etc. and further shows that they indeed can be interpreted one way or another. Specifically, VCA and ATGP are essentially the same algorithm in the sense that they both extract targets via maximal OP from a nested sequence of successive orthogonal subspace projection spaces. Copyright © 2013 Inderscience Enterprises Ltd. Copyright © 2013 Inderscience Enterprises Ltd.

关键词： Hyperspectral imaging

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A generalized directional Laplacian distribution: Estimation, mixture models and audio source separation

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IEEE Transactions on Audio, Speech and Language processing 2012年第9期20卷 2397-2408页

作者： Mitianoudis, Nikolaos Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace 67100 Xanthi Greece

Directional or Circular statistics are pertaining to the analysis and interpretation of directions or rotations. In this work, a novel probability distribution is proposed to model multidimensional sparse directional data. The Generalized Directional Laplacian Distribution (DLD) is a hybrid between the Laplacian distribution and the von Mises-Fisher distribution. The distribution's parameters are estimated using Maximum-Likelihood Estimation over a set of training data points. Mixtures of Directional Laplacian Distributions (MDLD) are also introduced in order to model multiple concentrations of sparse directional data. The author explores the application of the derived DLD mixture model to cluster sound sources that exist in an underdetermined instantaneous sound mixture. The proposed model can solve the general K × L (K

关键词： Source separation

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COMPRESSIVE SENSING-BASED image DENOISING USING ADAPTIVE MULTIPLE SAMPLING AND OPTIMAL ERROR TOLERANCE

COMPRESSIVE SENSING-BASED IMAGE DENOISING USING ADAPTIVE MUL...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Wonseok Kang Eunsung Lee Eunjung Chea Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Seoul Chung-Ang University Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479903573

In this paper, we present a compressive sensing-based image denoising algorithm using spatially adaptive image representation and estimation of optimal error tolerance based on sparse signal analysis. The proposed method performs block-based multiple compressive sampling after decomposing the sparse signal into feature and non-feature regions using simple statistical analysis. For minimization of recovery error and number of iterations, the modified OMP method estimates the optimal error tolerance using the average variance in the recovery step. Experimental results demonstrate that the proposed denoising algorithm better removes noise without undesired artifacts than existing state-of-the-art methods in terms of both objective (PSNR/SSIM) and subjective measures. processing time of the proposed method is 5 to 10 times faster than the standard OMP-based method.

关键词： Tolerances physiologic tolerance Sampling system recovery image denoising image representation images Signal analysis Statistical analysis Statistical methods image denoising algorithm

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