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检索条件"主题词=detection algorithms"

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detection of the First and Second Heart Sound Using Heart Sound Energy

Detection of the First and Second Heart Sound Using Heart So...

引用

International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Xinpei Wang Yuanyang Li Churan Sun Changchun Liu School of Control Science and Engineering Shandong University Jinan Shandong China

ISBN: (纸本)9781424441327

detection of the primary sound components in heart sound signal is the first step in automated diagnosis of cardiac abnormality. Although most existing heart sound detection algorithms perform well in normal signals, they usually have no effect on signals with heart murmurs. In this paper, an algorithm based on energy is proposed for robust detection of the first and second heart sound. It improved preprocessing and energy formula in envelope-based algorithm to overcome the interference of noises, which include heart murmurs and background noises, and can detect the accurate boundaries of the first and second heart sounds by constructing time gates. The algorithm has been tested using normal and abnormal clinical data and compared with the normalized average Shannon energy algorithm. The results show that the algorithm has over 96 percent correct ratio. That is superior to the normalized average Shannon energy algorithm.

关键词： detection algorithms NASA Heart valves Cardiac disease Acoustic noise Background noise Testing Cardiovascular diseases Frequency Sun

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Age-independent seizure detection

Age-independent seizure detection

引用

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

作者： Stephen Faul Andriy Temko William Marnane Department of Electrical Engineering University College Cork Ireland

This paper examines whether an appropriate algorithm, developed for use with neonatal data, could also be used, without alteration, for the detection of seizures in adults with epilepsy. The performance of a feature extraction and SVM classifier system is evaluated on databases of 17 neonatal patients and 15 adult patients. Mean ROC curve areas of 0.96 and 0.94 for neonatal and adult databases respectively show that high accuracy can be achieved independent of age. It is also shown that features contribute differently for neonatal and adult data.

关键词： Pediatrics Electroencephalography detection algorithms Epilepsy Spatial databases Signal processing algorithms Feature extraction Testing Biomedical signal processing USA Councils

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An Energy detection Algorithm Based on Double-Threshold in Cognitive Radio Systems

An Energy Detection Algorithm Based on Double-Threshold in C...

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International Conference on Information Science and Engineering (ICISE)

作者： Jinbo Wu Tao Luo Guangxin Yue Laboratory of Wireless Communication Systems and Networks School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424449095

Based on conventional single-threshold energy detection algorithm, we put forward a double-threshold version in cognitive radio system, and then, we analyze the detection probability, false alarm probability, miss probability and their relationships. For further research, we define two parameters for performance evaluation: the probability of collision between the cognitive user and the primary user, and the probability of spectrum unavailable to the cognitive user. Comparing to the single-threshold energy detection algorithm, both analysis and simulation results show that the proposed double-threshold energy detection algorithm can make a lower collision probability between the cognitive user and the primary user, despite a little increasing of the spectrum unavailable probability.

关键词： detection algorithms Cognitive radio Algorithm design and analysis Power engineering and energy Gamma ray detection Gamma ray detectors Information science Laboratories Wireless communication Postal services

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A Fast Void detection Algorithm for Three-Dimensional Deposition Simulation

A Fast Void Detection Algorithm for Three-Dimensional Deposi...

引用

International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)

作者： Otmar Ertl Siegfried Selberherr Institute of Microelectronics Technical University of of Vienna Wien Austria

We present an efficient algorithm for the detection of voids which potentially emerge during deposition process simulation. The application of modern level set techniques and data structures enables the fast determination of connected components directly from the implicit level set representation without the need of an additional surface extraction. The algorithm exhibits optimal linear scaling with surface size and is demonstrated on an example, where an isotropic etching process followed by conformal deposition is simulated.

关键词： detection algorithms Surface topography Level set Computational modeling Narrowband Data structures Microelectronics Difference equations Finite difference methods Area measurement

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Local approach to orthogonal subspace-based target detection in hyperspectral images

Local approach to orthogonal subspace-based target detection...

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Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Stefania Matteoli Nicola Acito Marco Diani Giovanni Corsini Dipartimento di Ingegneria dell'Informazione Università di Pisa Pisa Italy Accademia Navale Livorno Italy

Airborne or satellite hyperspectral sensing has proven valuable in many target detection applications, thanks to the dense spectral sampling of the sensed data, which provides a high material discriminability. Within this framework, this paper focuses on detection algorithms that rely upon subspace-based characterization of background. Whereas background subspace estimation has been typically accomplished through a global approach, which employs the whole image, a local methodology is here adopted. In fact, most of the interference affecting targets derives from the background materials in which they are inserted. Such a background interference lies in a subspace that is more likely spanned by the spectra of the pixels in the target neighborhood, rather than by endmembers/eigenvectors extracted from the whole image. Real hyperspectral imagery from the HyMap sensor is used to experimentally compare both global and local approaches to background subspace estimation. On this data, which exemplifies a mixed-pixel cluttered detection problem, detection results were strongly in favor of the local approach.

关键词： Object detection Hyperspectral imaging Hyperspectral sensors Interference Satellites Image sampling detection algorithms Pixel Data mining Image sensors

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An Improved Endpoint detection Algorithm with Low Signal-to-Noise Ratio

An Improved Endpoint Detection Algorithm with Low Signal-to-...

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

作者： Wang Yue Qian Zhihong Wang Xiuli College of Communication Engineering Jilin University China

An endpoint detection algorithm that combines expanded spectral subtraction with the SAP (speech absence probability) soft decision is proposed based on traditional methods. The algorithm employs a method of expanded spectral subtraction based on the noise compensation structure, which can estimate the noise during speech presence. A method of endpoint detection based on the SAP soft decision is given, which improves robustness and precision of endpoint detection. The experiments show that better performance can be obtained even if SNR is equal to -10 dB whereas such performance cannot be achieved by traditional energy-based methods with the same SNR.

关键词： detection algorithms Signal to noise ratio Speech enhancement Background noise Automatic speech recognition Working environment noise Noise robustness Detectors Degradation Speech recognition

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An Adaptive Corner detection Algorithm for Remote Sensing Image Based on Curvature Threshold

An Adaptive Corner Detection Algorithm for Remote Sensing Im...

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Congress on Image and Signal Processing, CISP

作者： Xiaolian Deng Yuehua Huang Shengqin Feng Changyao Wang

An adaptive corner detection algorithm for remote sensing image was discussed in this paper. The main proposal of this paper was to detect corner of remote sensing image automatically and intelligently. This paper proposed a novel corner detection algorithm, which confirmed the direction of corner by analyzing eight neighborhood direction gray gradients, then adopted the neighborhood gray gradient tracking method and two thresholds of gray gradient was adopted to detect the correct corner. By this corner detection method, corner of remote sensing image could be extracted correctly. Meanwhile, the threshold of discriminant function could be determined adaptively by calculating probability density curvature extremum of gray gradient instead of traditional empirical threshold. The result of the experiment demonstrated that, the algorithm could detect valuable ground control point, it had more detection accuracy and efficiency, and it had more adaptability and applicable prospect. The result of ground control point detection was more objective and dependable.

关键词： detection algorithms Remote sensing Image matching Automatic control Laboratories Geology Hazards Reservoirs Algorithm design and analysis Image processing

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Optimizing Network Anomaly detection Scheme Using Instance Selection Mechanism

Optimizing Network Anomaly Detection Scheme Using Instance S...

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GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

作者： Yang Li Tian-Bo Lu Li Guo Zhi-Hong Tian Lin Qi Institute of Computing Technology Chinese Academy and Sciences Beijing China Beijing University of Posts and Telecommunications Beijing China Harbin Institute of Technology Harbin China University of Maryland College Park MD USA

Network anomaly detection is a classically difficult research topic in intrusion detection. However, existing research has been solely focused on the detection algorithm. An important issue that has not been well studied so far is the selection of normal training data for network anomaly detection algorithm, which is highly related to the detection performance and computational complexity. Based on our previous proposed TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) anomaly detection method, which can detect anomalies with high detection rate and low false positive rate, we develop an instance selection mechanism for TCM-KNN based on EFCM (Extended Fuzzy C-Means) clustering algorithm in this paper, aiming at limiting the size of training dataset, thus reducing the computational cost of TCM-KNN and boosting its detection performance. We report the experimental results over real network traffic. The results demonstrate the instance selection method presented in this paper is effective for TCM-KNN and thus optimizing it as an effectively lightweight network anomaly detection scheme.

关键词： Intrusion detection detection algorithms Telecommunication traffic Computational efficiency Boosting Optimization methods Testing Computers Mobile computing Educational institutions

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Consensus-based distributed detection algorithm in wireless ad hoc networks

Consensus-based distributed detection algorithm in wireless ...

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International Conference on Signal Processing and Communication Systems, ICSPCS

作者： Gang Xiong Shalinee Kishore Department of Electrical and Computer Engineering Lehigh University Bethlehem PA USA

This paper presents the consensus-based distributed detection (CBDD) algorithm for wireless ad hoc networks, where no fusion center is involved in collecting local information and all nodes reach global decision consensus based on local information exchange. The convergence properties and probability of error of the CBDD algorithm are investigated assuming independent and identically distributed (i.i.d.) Gaussian observations with shifted mean under both an ideal and practical multiaccess (MAC) channel. Specifically, with appropriate algorithm design, there exists an optimal number of iterations that yields the minimum probability of error. Finally, simulation results are provided to verify these analytical results.

关键词： detection algorithms Mobile ad hoc networks Peer to peer computing Convergence Statistical distributions AWGN Algorithm design and analysis Object detection Feedback Nearest neighbor searches

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detection Algorithm for V-BLAST Systems with Novel Interference Cancellation Technique

Detection Algorithm for V-BLAST Systems with Novel Interfere...

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IEEE Conference on Vehicular Technology (VTC)

作者： Kai Wu Lin Sang He Wang Cong Xiong Dacheng Yang Xin Zhang Wireless Theories and Technologies Laboratory (WT&T) Beijing University of Posts and Telecommunications Beijing China

In the conventional zero-forcing ordered successive interference cancellation (ZF-OSIC) or minimum mean square error ordered successive interference cancellation (MMSE-OSIC) detection algorithm of vertical Bell-Labs layered space-time (V-BLAST) architecture, there exists an undesirable processing delay due to the calculation of the matrix pseudo-inverse and power reordering in detecting the symbol in each layer. The parallel interference cancellation (PIC) algorithm has a lower processing delay but poorer performance. Based on the features of SIC and PIC algorithms, an integrated PIC and OSIC detection (IPOD) algorithm is proposed which can lower the complexity as well as the processing delay of the whole algorithm with little performance loss. Moreover, there is an alterable parameter in IPOD algorithm which can be changed to obtain different trade off between complexity and performance. Thus, the proposed algorithm is more feasible for practical applications.

关键词： detection algorithms Interference cancellation Delay Portable media players Maximum likelihood estimation Throughput Wireless communication Bandwidth Receiving antennas Power system reliability

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