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检索条件"主题词=detection algorithms"

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Low power real-time seizure detection for ambulatory EEG

Low power real-time seizure detection for ambulatory EEG

引用

International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth

作者： Kunjan Patel Chern-Pin Chua Stephen Fau C. J. Bleakley Complex and Adaptive Systems Laboratory University College Dublin Dublin Ireland University College Cork National University of Ireland Cork IE

Ambulatory Electroencephalograph (AEEG) technology is becoming popular because it facilitates the continuous monitoring of epilepsy patients without interrupting their routine life. As long term monitoring requires low power processing on the device, a low power real time seizure detection algorithm suitable for AEEG devices is proposed herein. The performance of various classifiers was tested and the most effective was found to be the Linear Discriminant Analysis classifier (LDA). The algorithm presented in this paper provides 87.7 (100-70.2)% accuracy with 94.2 (100-78)% sensitivity and 77.9 (100-52.1)% specificity in patient dependent experiments. It provides 76.5 (79.0-73.3)% accuracy with 90.9 (96.2-85.8)% sensitivity and 59.5 (70.9-52.6)% specificity in patient independent experiments. We also suggest how power can be saved at the lost of a small amount of accuracy by applying different techniques. The algorithm was simulated on a DSP processor and on an ASIC and the power estimation results for both implementations are presented. Seizure detection using the presented algorithm is approximately 100% more power efficient than other AEEG processing methods. The implementation using an ASIC can reduce power consumption by 25% relative to the implementation on a DSP processor with reduction of only 1% of accuracy.

关键词： Electroencephalography Patient monitoring Linear discriminant analysis Digital signal processing Application specific integrated circuits Epilepsy detection algorithms Testing Brain modeling Energy consumption

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An Improved Algorithm for Harris Corner detection

An Improved Algorithm for Harris Corner Detection

引用

Congress on Image and Signal Processing, CISP

作者： Zhiyong Ye Yijian Pei Jihong Shi School of Information Yunnan University Kunming China

Corner points are formed from two or more edges and edges usually define the boundary between two different objects or parts of the same objects. In this novel we discuss the theory of the Harris corner detection and indicate its disadvantage. Then it proposes an improved algorithm of Harris detection algorithm based on the neighboring point eliminating method. It reduces the time of the detection, and makes the corners distributing more homogenous so that avoids too many corners stay together. Experimental results show that the algorithm can detect corner more equality distributing, and can be used in some fact applications such as image registration well.

关键词： Image edge detection detection algorithms Eigenvalues and eigenfunctions Image registration Autocorrelation Object detection Feature extraction Clustering algorithms Change detection algorithms Brightness

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Microscopic Cell Segmentation and Dead Cell detection Based on CFSE and PI Images by Using Distance and Watershed Transforms

Microscopic Cell Segmentation and Dead Cell Detection Based ...

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Eric Dahai Cheng Subhash Challa Rajib Chakravorty Victoria Research Laboratory National Information and Communication Technologies Australia Department of Electrical and Electronic Engineering University of Melbourne VIC Australia

Automatic cell segmentation and dead cell detection in microscopic images play a very important role in the study of the behaviour of lymphocytes. In this paper, a distance and watershed transforms based cell segmentation algorithm has been proposed to segment cells by using CFSE image, and a dead cell detection algorithm is also proposed to detect cell dead event. Experimental results have shown that the proposed algorithms are pretty robust to variable contrast microscopy image data, and variable cell densities, and the average cell detection rate has reached 93% with the average miss detection rate about 7%, and extremely low average false detection rate of 0.7%, and the dead cell rate is about 11%.

关键词： Microscopy Image segmentation Cells (biology) Immune system detection algorithms Event detection Robustness Diseases Image analysis Information analysis

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Automatic detection of premature ventricular contraction beat using morphological transformation and cross-correlation

Automatic detection of premature ventricular contraction bea...

引用

International Conference on Signal Processing and Communication Systems, ICSPCS

作者： Shamsun Nahar Md. ShahNoor bin Munir Department of Electrical & Electronic Engineering United International University Dhaka Bangladesh Department of Electrical & Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

This paper presents a premature ventricular contraction beat (PVC) detection algorithm based on morphological transformation and cross-correlation technique. A modified morphological filtering (MMF) technique is used for signal preprocessing and multiscale morphological derivative (MMD) is performed on the MMF conditioned signal to detect each ECG beat present in the signal. A template beat is chosen and compared with the rest ECG beats using cross-correlation technique. PVC beats are then detected using a decision parameter which is a linear function of two equally weighted indices. One of the indices is linearly dependent on inter-beat duration and the other is an exponential function of the cross-correlation coefficient between template beat and the ECG beat. Potential of this proposed method was examined using MIT-BIH arrhythmia database. Results show high sensitivity (96.67%) and specitivity (95.2%) on premature beat recognition.

关键词： Heart rate variability Electrocardiography detection algorithms Filtering Signal detection Shape Testing Signal processing Detectors Paper technology

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Cluster-Based Congestion Outlier detection Method on Trajectory Data

Cluster-Based Congestion Outlier Detection Method on Traject...

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Xia Ying Zhang Xu Wang Guo Yin School of Information Science and Technology Southwest Jiaotong University Chengdu China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

As the collection of moving object data become much easier, event-based outlier detection such as congestion in trajectory data are becoming increasingly attractive to data mining community. Most of the existing methods only perform the trajectory outlier detection on the spatial information. In this paper, a framework for congestion outlier detection with clustering method was proposed. Trajectory data are analyzed according to both temporal and spatial factors by introducing the concept of minimal bounding boxes (MBBs), and super dense clusters are regarded as congestion outliers. Experiments show the capability and efficiency of the proposed approach.

关键词： Telecommunication congestion control Object detection Educational institutions Computer science detection algorithms Intelligent transportation systems Fuzzy systems Information science Electronic mail Data mining

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An Enhanced Energy detection Algorithm in Cognitive Radio

An Enhanced Energy Detection Algorithm in Cognitive Radio

引用

International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Junwei Hao Yunxiao Zu School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China

As the rapid growth of wireless technologies, current spectrum scarcity has become a serious problem as more and more wireless applications compete for very little spectrum. On the other hand, some licensed bands allocated to applications such as TV services show little usage. Then, to improve the utilization of radio spectrum, cognitive radio technology has been proposed, so that devices can sense and use idle bands dynamically by autonomous detection. This paper mainly introduce an enhanced energy detection algorithm based on some usual methods for detecting signals embedded in noise, and then give the simulation results.

关键词： detection algorithms Cognitive radio Detectors Signal processing Signal detection Random processes AWGN Power engineering and energy Matched filters Computer vision

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Scene change detection algorithm on specific movie

Scene change detection algorithm on specific movie

引用

International Conference on Advanced Communication Technology (ICACT)

作者： Myoung-Beom Chung Il-Ju Ko Dae-Sik Jang Department of Media Soongsil University South Korea Department of Computer Information Engineering Kunsan University South Korea

Scene detection is pretreatment to index video information in video search system, and it is very important technology for overall performance. Existing scene detection used single characteristic of pixel value difference, histogram difference, etc or mixed single characteristics. However, accuracy of those is poor for specific video such as infrared camera, night shooting. This paper is proposed the method that is mixed color histogram and KLT algorithm for scene detection at the specific movie. We did an experiment which used color histogram only and KLT algorithm with color histogram. In result, proposed method is improved about 11.4% at the specific movie.

关键词： Layout detection algorithms Motion pictures Histograms Change detection algorithms Cameras Karhunen-Loeve transforms Indexing User-generated content Infrared detectors

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Joint channel estimation and data detection for OFDM systems over doubly selective channels

Joint channel estimation and data detection for OFDM systems...

引用

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Lanlan He Shaodan Ma Yik-Chung Wu Tung-Sang Ng Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China

In this paper, a joint channel estimation and data detection algorithm is proposed for OFDM systems under doubly selective channels (DSCs). After representing the DSC using Karhunen-Loe¿ve basis expansion model (K-L BEM), the proposed algorithm is developed based on the expectation-maximization (EM) algorithm. Basically, it is an iterative algorithm including two steps at each iteration. In the first step, the unknown coefficients in K-L BEM are first integrated out to obtain a function which only depends on data, and meanwhile, a maximum a posteriori (MAP) channel estimator is obtained. In the second step, data are directly detected by a novel approach based on the function obtained in the first step. Moreover, a Bayesian Cramer-Rao Lower Bound (BCRB) which is valid for any channel estimator is also derived to evaluate the performance of the proposed channel estimator. The effectiveness of the proposed algorithm is finally corroborated by simulation results.

关键词： Channel estimation OFDM Iterative algorithms detection algorithms Time-varying channels Detectors Intersymbol interference Helium Data engineering Multiaccess communication

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Partial OSIC detection for V-BLAST Systems

Partial OSIC Detection for V-BLAST Systems

引用

Pacific-Asia Conference on Circuits, Communications and Systems, PACCS

作者： Danping Li Hailin Zhang State Key Laboratory of Integrated Service Networks Xidian University Xi'an China

As a promising MIMO spatial multiplexing scheme, Vertical Bell Laboratories layered space-time (V-BLAST) can achieve high channel capacity without any increase in bandwidth and transmission power. In this paper a partial ordered successive interference cancellation detection scheme is proposed to reduce the high computational complexity and large system delay caused by the pseudo inverse of channel matrix and the ordering process in the conventional OSIC algorithm. Some layers are sorted in the descending order and P-layerspsila OSIC is employed. The received signal after interference cancellation passes through linear equalization or parallel interference cancellation with low complexity. Simulation results for the proposed algorithm with zero-forcing and MMSE criterion show that the proposed algorithm can decrease the computational complexity without performance loss.

关键词： Interference cancellation Receiving antennas Computational complexity Signal processing algorithms Transmitting antennas Interference suppression MIMO detection algorithms Channel capacity Bandwidth

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An Early Fire Image detection and Identification Algorithm Based on DFBIR Model

An Early Fire Image Detection and Identification Algorithm B...

引用

Computer Science and Information Engineering, CSIE, WRI World Congress on FLAGGED

作者： Chen Jun Du Yang Wang Dong Dept. of Petroleum Supply Engineering Logistical Engineering University Chongqing China

An algorithm of early fire image detection and identification based on discrete fractal Brownian incremental random field model (DFBIR) is proposed in this paper. The flame color brightness and motion clues are chosen as the imprint of the fire image. At first, the suspicious fire region is detected by the flame color model. And the differential model is used to analyze if the suspicious fire region extends. If the suspicious region extends, the early fire image is further detected and identified by the algorithm of DFBIR model. The algorithm can exclude the mendacious fire and detect the real fire in three steps as follows. First, the size of the rectangular window is confirmed. Second, the fractal dimension and the fractal deviation are computed. Third, the migratory window calculation is done to make a final decision. The experimental results show that the algorithm can successfully detect and identify fire.

关键词： Fires Fractals Brightness Image color analysis Space technology Smoke detectors Computer science Petroleum detection algorithms Neural networks

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