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Histogram equalization using a reduced feature set of background speakers’ utterances for speaker recognition Article

Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 738-750 doi: 10.1631/FITEE.1500380

Abstract: We propose a method for histogram equalization using supplement sets to improve the performance of speakerThe ranks of sample values for histogram equalization are estimated in ascending order from both themethods, such as cepstral mean normalization (CMN), cepstral mean and variance normalization (MVN), histogramequalization (HEQ), and the European Telecommunications Standards Institute (ETSI) advanced front-end

Keywords： Speaker recognition     Histogram equalization     i-vector    

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DE-CMA：An Improved Blind Equalization Algorithm Used in3G Connection Systems

Wang Ji,Hu Aiqun,Song Yubo

Strategic Study of CAE 2007, Volume 9, Issue 2,   Pages 54-57

Abstract:

The convergence of the Constant-modulus algorithm widely used in DVB system is a complex problem.Firstly,some influencing factors such as cost function,iterative equation and filter coefficients are considered;then,in this paper,an ameliorative algorithm with time-delay estimate is proposed,which can avoid converging to the ill solution by correcting the position of main path.Simulation results demonstrate the proposed algorithm can highly improve the convergence performance of the primary one.Besides,its simplicity and efficiency make it feasible in the high-rate 3G connection application.

Keywords： blind equalization     CMA     ill-convergence     time-delay-estimate    

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Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems

Yong-xing LIU,Ken-li LI,Zhuo TANG,Ke-qin LI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 7,   Pages 519-531 doi: 10.1631/FITEE.1400399

Abstract: With the increasing energy consumption of computing systems and the growing advocacy for green computing, energy efficiency has become one of the critical challenges in high-performance heterogeneous computing systems. Energy consumption can be reduced by not only hardware design but also software design. In this paper, we propose an energy-aware scheduling algorithm with equalized frequency, called EASEF, for parallel applications on heterogeneous computing systems. The EASEF approach aims to minimize the finish time and overall energy consumption. First, EASEF extracts the set of paths from an application. Then, it reconstructs the application based on the extracted set of paths to achieve a reasonable schedule. Finally, it adopts a progressive way to equalize the frequency of tasks to reduce the total energy consumption of systems. Randomly generated applications and two real-world applications are examined in our experiments. Experimental results show that the EASEF algorithm outperforms two existing algorithms in terms of makespan and energy consumption.

Keywords： Directed acyclic graph     Dynamic voltage scaling     Energy aware     Heterogeneous systems     Task scheduling    

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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 149-156 doi: 10.1007/s11465-010-0008-y

Abstract: With the automation development of manufacturing processes, artificial intelligence technology has been gradually employed to increase the automation and intelligence degree in quality control using statistical process control (SPC) method. In this paper, an SPC method based on a fuzzy adaptive resonance theory (ART) neural network is presented. The fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms, which shows that the fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. At the same time, combined with spectrum analysis of the autoregressive model of quality parameters, the fuzzy ART neural network can also be utilized to adaptively detect the abnormal patterns in the control chart.

Keywords： statistical process control (SPC)     fuzzy adaptive resonance theory (ART)     histogram     control chart     time    

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Frequency-domain Analysis of ECG Signals

Tu Chengyuan,Zeng Yanjun,Li Shuxin

Strategic Study of CAE 2002, Volume 4, Issue 12,   Pages 66-70

Abstract:

A new simple approach to effectively detect QRS — T complexes in ECG curve is described, so as to easily get the P-wave (when AF does not happen) or the f-wave (when AF happens). By means of signal processing techniques such as the power spectrum function, the auto-correlation function and cross-correlation function, two kinds of ECG signals when AF does or does not happen were successively analyzed, showing the evident differences between them.

Keywords： ECG curve     P-wave     f-wave     AF (atrial fibrillation)     histogram     power spectrum     autocorrelation     cross-correlation    

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FM Radio Based Non-cooperative Bistatic Radar Experimental System

Wang Yan

Strategic Study of CAE 2007, Volume 9, Issue 11,   Pages 39-42

Abstract:

An experimental FM radio based non-cooperative bistatic radar is briefly described,  and two related key techniques,  i. e. line-of-sight (LOS) signal cancellation and targets detection,  are listed in this paper.  Other than algorithms appeared in most papers,  NLMS based non-causal filters are used to equalize the array multi-channel differences.  The LOS signal about 80 dB above the noise level is cancelled completely after joint time-space processing.  Civil airplanes are detected 300 km away.  Experimental data verifies the simplicity and effectiveness of the proposed method.

Keywords： FM radio     non-cooperative bistatic radar     LOS signal     equalization     DBF    

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A Comprehensive Approach for the Clustering of Similar-Performance Cells for the Design of a Lithium-Ion Battery Module for Electric Vehicles Article

Wei Li, Siqi Chen, Xiongbin Peng, Mi Xiao, Liang Gao, Akhil Garg, Nengsheng Bao

Engineering 2019, Volume 5, Issue 4,   Pages 795-802 doi: 10.1016/j.eng.2019.07.005

Abstract:

An energy-storage system comprised of lithium-ion battery modules is considered to be a core component of new energy vehicles, as it provides the main power source for the transmission system. However, manufacturing defects in battery modules lead to variations in performance among the cells used in series or parallel configuration. This variation results in incomplete charge and discharge of batteries and non-uniform temperature distribution, which further lead to reduction of cycle life and battery capacity over time. To solve this problem, this work uses experimental and numerical methods to conduct a comprehensive investigation on the clustering of battery cells with similar performance in order to produce a battery module with improved electrochemical performance. Experiments were first performed by dismantling battery modules for the measurement of performance parameters. The k-means clustering and support vector clustering (SVC) algorithms were then employed to produce battery modules composed of 12 cells each. Experimental verification of the results obtained from the clustering analysis was performed by measuring the temperature rise in the cells over a certain period, while air cooling was provided. It was found that the SVC-clustered battery module in Category 3 exhibited the best performance, with a maximum observed temperature of 32 ℃. By contrast, the maximum observed temperatures of the other battery modules were higher, at 40 ℃ for Category 1 (manufacturer), 36 ℃ for Category 2 (manufacturer), and 35 ℃ for Category 4 (k-means-clustered battery module).

Keywords： Clustering algorithm     Battery module     Equalization     Electric vehicle    

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Detection of engineering vehicles in high-resolution monitoring images

Xun Liu, Yin Zhang, San-yuan Zhang, Ying Wang, Zhong-yan Liang, Xiu-zi Ye,star.liuxun@gmail.com,yinzh@zju.edu.cn,syzhang@zju.edu.cn,maggiewang0427@gmail.com

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 5,   Pages 346-357 doi: 10.1631/FITEE.1500026

Abstract: This paper presents a novel formulation for detecting objects with articulated rigid bodies from high-resolution monitoring images, particularly . There are many pixels in high-resolution monitoring images, and most of them represent the background. Our method first detects object patches from monitoring images using a coarse detection process. In this phase, we build a descriptor based on histograms of oriented gradient, which contain color frequency information. Then we use a linear support vector machine to rapidly detect many image patches that may contain object parts, with a low false negative rate and a high false positive rate. In the second phase, we apply a refinement classification to determine the patches that actually contain objects. In this stage, we increase the size of the image patches so that they include the complete object using models of the object parts. Then an accelerated and improved salient mask is used to improve the performance of the dense scale-invariant feature transform descriptor. The detection process returns the absolute position of positive objects in the original images. We have applied our methods to three datasets to demonstrate their effectiveness.

Keywords： Object detection     Histogram of oriented gradient (HOG)     Dense scale-invariant feature transform (dense    

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Title Author Date Type Operation

Histogram equalization using a reduced feature set of background speakers’ utterances for speaker recognition

Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU

Journal Article

DE-CMA：An Improved Blind Equalization Algorithm Used in3G Connection Systems

Wang Ji,Hu Aiqun,Song Yubo

Journal Article

Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems

Yong-xing LIU,Ken-li LI,Zhuo TANG,Ke-qin LI

Journal Article

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Journal Article

Frequency-domain Analysis of ECG Signals

Tu Chengyuan,Zeng Yanjun,Li Shuxin

Journal Article

FM Radio Based Non-cooperative Bistatic Radar Experimental System

Wang Yan

Journal Article

A Comprehensive Approach for the Clustering of Similar-Performance Cells for the Design of a Lithium-Ion Battery Module for Electric Vehicles

Wei Li, Siqi Chen, Xiongbin Peng, Mi Xiao, Liang Gao, Akhil Garg, Nengsheng Bao

Journal Article

Detection of engineering vehicles in high-resolution monitoring images

Xun Liu, Yin Zhang, San-yuan Zhang, Ying Wang, Zhong-yan Liang, Xiu-zi Ye,star.liuxun@gmail.com,yinzh@zju.edu.cn,syzhang@zju.edu.cn,maggiewang0427@gmail.com

Journal Article