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On Sequential P Systems with Proteins

On Sequential P Systems with Proteins

引用

2011 International Conference on Future Management Science and Engineering(ICFMSE 2011)

作者： Chun Lu Xiao-jie Chen Xiao-long Shi Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology

Membrane computing identifies an unconventional computing model,namely a P system,from natural phenomena of objects evolutions and chemical reactions in the living *** the nature of maximal parallelism in this model,P systems have a great potential for implementing massively concurrent systems as an efficient computing *** systems with proteins on membranes(MP systems,for short) are a variant of P systems paying a more attention to the proteins on *** the original definition of MP systems,rules are also called to be applied in a maximally parallel ***,in some cases a sequential model may be a more reasonable *** this work,we study the computational power of sequential MP systems and look at MP systems operating on multisets of objects and *** show that they are equivalent to vector addition systems.

关键词： Membrane computing,Membrane system,Membrane protein,Sequential system,Vector addition system

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Superiority of the 3rd order approximation model to the 2nd order in Diffusion Kurtosis Imaging

Superiority of the 3rd order approximation model to the 2nd ...

引用

作者： Iraji, Armin Davoodi-Bojd, Esmaeil Soltanian-Zadeh, Hamid Hossein-Zadeh, Gholam-Ali Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI 48202 United States

ISBN: (纸本)9789644634284

For estimating the kurtosis parameter in Diffusion Kurtosis Imaging (DKI), usually second order expansion of the diffusion signal is used in conventional acquisition data. However, in this work, we show that this is not sufficient and should be reconsidered. Instead of using the second order expansion, we propose to use the third order expansion. At first, we show that the third order term of the Taylor's expansion has considerable values compared to second and first terms for the conventional b-values used in DKI. Then, for proving our claim empirically, we use real data to compare the proposed model with the previous one. To this end, five regions of the brain are extracted and for each region the fitting errors of both models are computed. The results confirm that the fitting error of the third order model is always (for all regions) less than the second order model. Although the improvement of the fitting error seems to be small, but considering the sensitivity analysis, this improvement can enhance the estimation of kurtosis. The resulting maps of the kurtosis parameter show this enhancement. The white matter in the map of third order model is more distinguishable than in the other model. © 2011 AmirKabir Univ of Tech.

关键词： Diffusion

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Spectral clustering based unsupervised change detection in SAR images

Spectral clustering based unsupervised change detection in S...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiangrong Zhang Zemin Li Biao Hou Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

An unsupervised change detection method based on spectral clustering and difference image methods for multitemporal single-channel single-polarization synthetic aperture radar (SAR) images is proposed. The difference image is generated by integrating the typical difference image method with Non-Local Filter, which exploits both the spatial neighborhood information and gray similarity information, and can well reduce the speckle noises of SAR images. The spectral clustering algorithm is employed to cluster the difference image into two clusters and get the change map. Compared with traditional clustering algorithms, such as A-means, SC can recognize the clusters of unusual shapes and obtain the globally optimal solutions. Experimental results confirm the effectiveness of the proposed techniques.

关键词： Clustering algorithms Remote sensing Principal component analysis Change detection algorithms Synthetic aperture radar Sensors Noise

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Partial Differential Equation Model Method Based on image Feature for Denoising

Partial Differential Equation Model Method Based on Image Fe...

引用

International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Xiaohua Zhang Ran Wang L. C. Jiao Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

For the special different nature images, we could hardly find particularly desirable approach, and there always exist Gibbs-type artifacts in the results of most methods. A novel Partial Differential Equation (PDE) model is proposed based on image feature for images denoising. The PDE model is adaptive within each region according to the details of the image feature to adjust the size of the diffusion coefficient. So it can be disposed the high gradient noise at the same time better to retain the edge information. We also analyze the performance of the PDE model method. Numerical results show that our algorithm competes favorably with state of the-art TV projection methods to eliminate noise and reduce Gibbs-type artifacts.

关键词： Mathematical model TV image edge detection Noise reduction Noise Noise measurement Numerical models

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image Denoising with Non-Local Means in the Shearlet Domain

Image Denoising with Non-Local Means in the Shearlet Domain

引用

International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Xiaohua Zhang Qiang Zhang L. C. Jiao Key Laboratory of Intelligent Perception and Image Understanding of the Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this paper, a novel method for image denoising is proposed which adopts multiscale geometry tool. Firstly the image is decomposed by discrete shearlet transform. The shearlet coefficients of each direction approach the generalized Gaussian distribution. We use the principal component analysis (PCA) for every similarity window of shearlet coefficients. Then we use Generalized Gaussian model of non-local means method to handle the shearlet coefficients. Finally, we reconstruct image with the new shearlet coefficients to obtain the result. Numerical results show that our algorithm competes favorably with nonlocal means algorithms in the case of high noise.

关键词： image denoising Transforms Pixel Principal component analysis Algorithm design and analysis Noise reduction Noise

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SAR image Despeckling via Spatially Constrained Multiscale Products

SAR Image Despeckling via Spatially Constrained Multiscale P...

引用

2011 IEEE CIE International Conference on Radar(2011年IEEE国际雷达会议RADAR 2011)

作者： X. L. Tian L. C. Jiao X. H. Zhang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

This paper presents a wavelet-based multiscale products scheme for synthetic aperture radar (SAR) image despeckling. A compactly supported quadratic spline function that approximates the first derivative of Gaussian is employed in the scheme to decompose log-transformed SAR images. The multiplied results of the decomposed coefficients of adjacent scales consist of multiscale products. The multiscale products can sharp the important structures while weakening noise. A spatially selective neighborhood technique by iteratively selecting neighborhood system in the multiscale products is introduced in searching the important structure information. The influence of the spatial information is imposed on the multiscale products, instead of on the wavelet coefficients, which improves the capability of identifying important features. Experiments show that the proposed scheme is better in SAR image despeckling and preserving edges and detail information than other waveletbased multiscale products methods.

关键词： Despeckling synthetic aperture radar multiscale products wavelet transform neighborhood system

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A Fully Implantable Stimulator with Wireless Power and Data Transmission for Experimental Use in Epidural Spinal Cord Stimulation

A Fully Implantable Stimulator with Wireless Power and Data ...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Qi Xu Jun Li Wenjuan Han Houlun Zhou Key Laboratory of Image Processing and Intelligent Control Department of Control Science & Engineering Huazhong University of Science & Technology Department of Anatomy Tongji medical college Huazhong University of Science & Technology

ISBN: (纸本)9781424441211

Epidural spinal cord stimulation (ESCS) combined with partial weight bearing therapy (PWBT) has been reported to facilitate recovery of functional walking for individuals after chronic incomplete spinal cord injury. This paper describes a low cost, fully implantable, advanced ESCS stimulator that can be manufactured in a research laboratory for use in small animals. The system is composed of four main parts: an external personal digital assistant (PDA), an external controller, an implantable pulse generator (IPG), lead extension and electrode. The PDA allows the experimenter to program the stimulation parameters through a user-friendly graphical interface. The external controller placed on the rat back communicates with PDA via RF telemetry. The IPG generates the biphasic charge-balanced voltage-regulated pulses, which are delivered to the bipolar electrode by the lead extension to achieve chronic ESCS in freely moving rats. A RF carrier from the Class-E amplifier in the external controller provides both data and power for the implanted circuitry through a closely coupled inductive link. The IPG is hermetically packaged using a silicon elastomer and measures 22mm×23mm×7mm with a mass of ~3.78g.

关键词： Class-E amplifier Epidural spinal cord stimulation Incomplete spinal cord injury Inductive link Rat

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An analysis of the eigenvalues method for polarimetric SAR image classification

An analysis of the eigenvalues method for polarimetric SAR i...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： S. P. Gou Xin. Qiao L. C. Jiao Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this paper, we focus on the distribution of eigenvalues, and based on Gaussian assumption, then we do an analysis of the eigenvalues potential for POL-SAR classification. Generally, we use Gaussian mixture model to describe the distribution of the eigenvalue and Bayesian classifier to achieve the POL-SAR pixel classification. The method is tested with the NASA/JPL AIRSAR data.

关键词： Decision support systems

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Research on Fuzzy Enhancement in the Diagnosis of Liver Tumor from B-mode Ultrasound images

Research on Fuzzy Enhancement in the Diagnosis of Liver Tumo...

引用

International Conference on intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Wu Qiu Rui Wang Feng Xiao Mingyue Ding School of Life Science and Technololgy Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

Fuzzy enhancement is applied in computer aided diagnosis of liver cancer from B mode ultrasound images as a pre-processing procedure in this paper. It was evaluated with three classifiers including K means, back propagation neural network and support vector machine using 25 features from first order statistic (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), Grey level dependant matrix (GLDM) and LAWS. In the analysis of 166 normal liver tissue, 30 hemangioma and 60 malignant tumor, our method improved the classification accuracy of three classifiers (K means, BP neural network and support machine vector) in distinguishing liver cancer, hemangioma and normal liver cancer from B mode ultrasound images. It is proved that fuzzy enhancement as an efficient preprocessing procedure could be used in the computer aided diagnosis system of liver cancer.

关键词： Liver Cancer Ultrasonic imaging Feature extraction Artificial neural networks Accuracy Support vector machines

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Global asymptotic stability of fuzzy cellular neural networks with unbounded time-varying delays

Global asymptotic stability of fuzzy cellular neural network...

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International Conference on Information Science and Technology (ICIST)

作者： Chongjun Zhu Gang Bao College of Mathematics and Statistics Hubei Normal University Huangshi China Department of Control Science and Engineering Key Laboratory of Image Processing Intelligent Control of Education Ministry China Wuhan Hubei China

The global asymptotic stability of fuzzy cellular neural networks with unbounded time-varying delays and Lipschitz continuous activation functions is investigated in this brief. Based on the concept of comparison, som... 详细信息

ISBN: (纸本)9781424494408

关键词： Delay Asymptotic stability Cellular neural networks Circuit stability Artificial neural networks Stability analysis Circuits and systems

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