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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

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Attention State Assessment by Analyzing Electroencephalograph signals

Attention State Assessment by Analyzing Electroencephalograp...

引用

international congress on image and signal processing, biomedical engineering and informatics

作者： Junchang Zhao Xiaolin Huang Jun Wang Image Processing and Image Communications Key Lab Nanjing University of Posts & Telecomm Institute of Biomedical Electronic Engineering School of Electronic Science and Engineering Nanjing University

ISBN: (纸本)9781509037117

For brain function study, it is very important to assess the state of different attention conditions. In this paper, we study a cross-correlation between different attention electroencephalograph (EEG) signals by detrended cross-correlation analysis (DCCA). We use the method to study attention α wave EEG. And, we found that is possible to discriminate the cross-correlation between the meditation state of closing eyes and the absence of mind. It was found that the DCCA values of idle subjects' α wave EEG signals increased compared the meditating participants' α wave EEG signals. And it can be particularly helpful for treatment and brain development research.

关键词： meditation activity DCCA a wave

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Recognition algorithm for huge number of very similar objects

Recognition algorithm for huge number of very similar object...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Lingfeng Kong Qingxiang Wu College of Photonic and Electronic Engineering Fujian Normal University Fujian China Technology College of Photonic and Electronic Engineering Fujian Normal University Fujian China

ISBN: (纸本)9781509037117

In order to identify a large number of very similar objects, a novel recognition approach is proposed by mean of combination of two dynamic grouping algorithms, the visual processing mechanism, PCA and multi-pathway SVM. The samples have been segmented to appropriate groups by grouping features, and then features with rotation invariance and translation invariance of each group are extracted. Finally, the features' reduced by PCA are put into the SVM to build classification models. The experimental results show that the proposed algorithms in this paper error rates are obviously less than the algorithms in which samples not be grouped and put the classification features into SVM to build a classification model directly.

关键词： Classification algorithms Heuristic algorithms image color analysis Support vector machines Principal component analysis Training Transforms

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Ear recognition based on deep convolutional network

Ear recognition based on deep convolutional network

引用

international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Liang Tian Zhichun Mu School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9781509037117

Ear recognition is gaining on popularity in recent years. The human ear are neither affected by expressions like faces are nor do need closer touching like finger-prints do. In this paper, a novel algorithm was proposed to do ear recognition using deep convolutional neural network and provide a visualization of the learned network. We design a convolutional neural network with three convolutional layers, a fully-connected layer and a soft-max classifier. The experimental results on USTB ear database indict that our proposed method is easier botain high accuracy and outperforms the traditional method in dealing with partial occlusion.

关键词： Ear Training Neural networks Convolution Feature extraction image recognition Testing

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A new method of cognitive radio spectrum prediction research

A new method of cognitive radio spectrum prediction research

引用

international congress on image and signal processing, biomedical engineering and informatics

作者： Shujing Ni Xuemei Bai Zhijun Wang Bin Guo Changchun University of Science and Technology China Jilin Engineering Research Center of RFID and Intelligent Information Processing Changchun Normal University China

ISBN: (纸本)9781509037117

In order to improve the prediction accuracy of cognitive radio spectrum and providing more reliable spectrum access for the subsequent spectrum detection, the dynamic fuzzy neural network is applied to predict the cognitive radio spectrum, and prove its feasibility. Simulation results show that the algorithm has higher accuracy than the general spectral prediction algorithm.

关键词： channel state model cognitive radio system spectrum prediction dynamic fuzzy neural network

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Low Power Injection-Locked Frequency Divider Using Native MOS for biomedical Application

Low Power Injection-Locked Frequency Divider Using Native MO...

引用

international congress on image and signal processing, biomedical engineering and informatics

作者： Wen-Cheng Lai Sheng-Lyang Jang Ho Chang Lee Wei-Te Liu Dep. of Electronic Engineering National Taiwan University of Science and Technology

ISBN: (纸本)9781509037117

This proposal presents a 0.55V and low power divided-by-2 injection-locked frequency divider (ILFD) using native nMOS as the injection MOSFET with threshold voltage nearly equal to zero. The measured locking range is 6.1 to 7.45 GHz at injection power of OdBm. Excluding output buffers, the ILFD consumes the power 0.69 mW under a standard supply of 0.55 V for biomedical application.

关键词： native nMOS low power Locking range injection-locked frequency divider (ILFD)

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Bandwidth efficient design and channel estimation over time-varying fading environments

Bandwidth efficient design and channel estimation over time-...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Lihua Li Xianwen He Hao Zhang Department of Communication Engineering Naval University of Engineering Wuhan Hubei CN Naval University of Engineering Wuhan Hubei CN

ISBN: (纸本)9781509037117

In this paper, we consider bandwidth efficient design and channel estimation over time-varying frequency-selective environments, where the basis expansion model (BEM) is used to describe the time-varying channel. Superimposed training based channel estimation based affine precoding model is designed, where the data interference is eliminated from received data prior to performing channel estimation, while the training sequence is completely out in the symbol detection. Simulations results show that the proposed scheme can yield better detection performance with high bandwidth efficiency.

关键词： Training Channel estimation Precoding Time-varying channels Bandwidth Interference Estimation

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image post-processing of a quad-head combined aerial camera and its surveying application

Image post-processing of a quad-head combined aerial camera ...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhaorong Lin Na Yao Gaode Qin Hongxia Cui Research Office of Aerial Optical Remote Sensing Beijing Institute of Space Mechanics and Electricity Beijing China Shenzhen Polytechnic School of computer engineering Shenzhen China Department of Information Science and Technology Bohai University Jinzhou China

ISBN: (纸本)9781509037117

A quad-head combined aerial camera is first introduced in this paper. Due to its multiple center projection at each exposure station, an image post-processing procedure including camera calibration, matching, self-calibration stitching and color balancing is proposed to generate the stitched virtual image, in which the mathematical models of geometric calibration and self-calibration algorithms are primarily derived. The experiments show that the post-processing procedure has been capable of obtaining satisfying stitched virtual images. Besides, the related precisions of a 1:500 scale photogrammetry project has totally meet the requirements of national specifications of surveying and mapping.

关键词： Cameras Mathematical model Calibration Distortion Unmanned aerial vehicles Lenses Optical distortion

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Research of Three-Dimensional Indoor Positioning Based on RSSI

Research of Three-Dimensional Indoor Positioning Based on RS...

引用

international congress on image and signal processing, biomedical engineering and informatics

作者： Shan Liu Yufeng Ma Jianping Chai School of Information Engineering Communication University of China

ISBN: (纸本)9781509037117

This paper proposed a newly designed model to satisfy the growing demand of three-dimensional indoor positioning services. The existing different positioning services cannot meet the demand in our daily life, and the increasingly need of three-dimensional positioning services has attracted more attention. In this paper, we implement our analysis and research via studying the evaluation results of different indoor positioning models based on RSSI. Experimental results demonstrated that our proposed method of reducing the influences of environmental factors can greatly improve the positioning precise and reduce the positioning error.

关键词： Received signal strength indication Logarithm fading model Gaussian model

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A kind of effective method of removing compound noise in image

A kind of effective method of removing compound noise in ima...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Hongyan Chen Electronic Engineering College Chengdu University of Information Technology Chengdu China

ISBN: (纸本)9781509037117

The noise is generally not a single type in digital image, which is usually composed of Gaussian noise and pulse noise. So the signal to noise ratio of the image is low and the noise in images needs to be processed. The traditional denoising algorithm and various improved algorithm is effective for single Gaussian noise or impulse noise mostly, these denoising algorithms are unable to obtain satisfactory denoising effect in dealing with the mixed noise. Some existing hybrid denoising methods usually change distribution characteristics of another noise when removing one noise at the same time, so subsequent denoising effect is affected. To resolve the problem, a composite image denoising method based on the combination of independent component analysis and traditional spatial denoising method is proposed. Simulation experiment results show that the method can effectively preserve edge details and other information of image when removing mixed noise.

关键词： Noise reduction Gaussian noise Filtering Compounds Independent component analysis image edge detection Noise measurement

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Fast robust image restoration using a new neural fusion method?

Fast robust image restoration using a new neural fusion meth...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Youshen Xia College of Mathematics and Computer Science Fuzhou University Fuzhou China

ISBN: (纸本)9781509037117

This paper proposes a new neural fusion algorithm for fast robust image restoration without requiring the optimal regularization parameter. The new neural fusion algorithm is based on a new reduced dimension neural network (RDNN). The RDNN is guaranteed to obtain an optimal fusion weight. The proposed RDNN-based neural fusion algorithm uses only a very small solution space to compute the optimal fusion weight, unlike existing neural fusion algorithms with solution space dimension being grater than image size. Unlike current image restoration algorithms, the proposed neural fusion algorithm has a low-dimensional solution space Computed results show that the proposed new algorithm has a robust performance against non-Gaussian noise and can obtain a good image estimate at a fast speed by using the non-optimal regularization parameter.

关键词： image restoration signal processing algorithms Algorithm design and analysis Robustness Neural networks Estimation TV

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