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2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

作者： Zhiwei Nie School of Computer Science Guangdong University of Technology

ISBN: (纸本)9781510871076

A de-nosing approach is needed to eliminate the maternal heart sound and internal noise in the acquired fetal heart sound signal,but blind separation algorithm,as a conventional approach,does not perform well in the de-noising of fetal heart ***,a new fetal heart sound de-noising approach based on variational mode decomposition(VMD).Resampling is conducted for original signal on the basis of fetal heart sound signal characteristics,and then VMD is performed to select the signal components for independent component analysis with original signal,so as to obtain the denoised fetal heart sound *** revealed in experimental results,this approach achieves better de-noising than the conventional ***,it is a favorable de-noising approach to reduce the noise mixed in the original fetal heart sound signal,so as to improve the computational accuracy of fetal heart rate and provide the prerequisite for effective fetal heart monitoring.

关键词： Fetal heart sound variational mode decomposition jade algorithm de-noising

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Maximum Parallel Categories Approach for Determining the Optimal Number of Independent Components

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2025年 1-30页

作者： He, Kaili E, Jianwei Ye, Jimin Guangxi Minzu Univ Ctr Appl Math Guangxi Sch Math Sci Nanning 530006 Peoples R China Xidian Univ Sch Math & Stat Xian 710071 Peoples R China

Independent component analysis (ICA), as a statistical and computational method, has been receiving increasing attention to estimate the feature information of the observed signals. The determination of the optimal number of independent components (ICs) is perceived as a challenging task to work while operating the ICA approach. Up to present, the extant approaches for achieving the optimal number of the ICs have poor performance when the number of observed signals is less than the number of true signals and the observed signals are unstructured signals. This paper proposes a novel unsupervised method, maximum parallel categories approach (MPCA), for identifying the optimal number of the ICs. The proposed MPCA method begins with separating a series of ICs by running ICA algorithm repeatedly, followed by clustering the ICs into several categories via hierarchical clustering method. Then, the optimal number of the ICs can be determined as stable number of equivalence categories in cyclic clustering the ICs, corresponding to the maximum parallel categories of the ICs. The proposed method can not only adaptively determine the optimal number of the ICs without expert experience, but also give the stable categories for the estimated ICs. In simulations, the effectiveness and superiority of the proposed method are validated from the perspective of manmade signals and practical speech signals. Additionally, the sensitivity analysis of MPCA method is analyzed and verified based on the simulated signals.

关键词： Clustering Independent component analysis jade algorithm Optimal number of ICs Signal processing

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Multi-UAV Path Planning Based on Cooperative Co-Evolutionary algorithms with Adaptive Decision Variable Selection

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DRONES 2024年第9期8卷 435-435页

作者： Meng, Qicheng Qu, Qingjun Chen, Kai Yi, Taihe Natl Univ Def Technol Coll Syst Engn Changsha 410073 Peoples R China

When dealing with UAV path planning problems, evolutionary algorithms demonstrate strong flexibility and global search capabilities. However, as the number of UAVs increases, the scale of the path planning problem grows exponentially, leading to a significant rise in computational complexity. The Cooperative Co-Evolutionary algorithm (CCEA) effectively addresses this issue through its divide-and-conquer strategy. Nonetheless, the CCEA needs to find a balance between computational efficiency and algorithmic performance while also resolving convergence difficulties arising from the increased number of decision variables. Moreover, the complex interrelationships between the decision variables of each UAV add to the challenge of selecting appropriate decision variables. To tackle this problem, we propose a novel collaborative algorithm called CCEA-ADVS. This algorithm reduces the difficulty of the problem by decomposing high-dimensional variables into sub-variables for collaborative optimization. To improve the efficiency of decision variable selection in the collaborative algorithm and to accelerate the convergence speed, an adaptive decision variable selection strategy is introduced. This strategy selects decision variables according to the order of solving single-UAV constraints and multi-UAV constraints, reducing the cost of the optimization objective. Furthermore, to improve computational efficiency, a two-stage evolutionary optimization process from coarse to fine is adopted. Specifically, the Adaptive Differential Evolution with Optional External Archive algorithm (jade) is first used to optimize the waypoints of the UAVs to generate a basic path, and then, the Dubins algorithm is combined to optimize the trajectory, yielding the final flight path. The experimental results show that in four different scenarios involving 40 UAVs, the CCEA-ADVS algorithm significantly outperforms the Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Artificial Bee Colon

关键词： unmanned aerial vehicle (UAV) path planning Cooperative Co-Evolutionary algorithm decision variable jade algorithm

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Non-contact detection of human heart rate with Kinect

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第4-Sup期22卷 S8199-S8206页

作者： Zhou, Liqian Yin, Ming Xu, Xi Yuan, Xinpan Liu, Xiaojun Hunan Univ Technol Sch Comp Zhuzhou 412007 Peoples R China

Non-contact detection of heart rate has been addressed by researchers from very different fields. However, the low accuracy of measuring results in the difficulties in methodology deployment. This paper introduces the principle of heartbeat detection. A detection scheme by using Kinect is proposed. Further, the signal processing approach based on jade algorithm is developed to efficiently remove the clutter in mixture signals, and it enables accurate transforming via Z-score normalization. Due to the significances presented in this work, the detection error is 1.79%, when processed with the proposed algorithm. Experimental results are statistically analyzed, which makes it a promising basis for the realization of heart rate detection.

关键词： Kinect Heart rate jade algorithm Non-contact detection

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The improvement of change detection from multi-date satellite images using the source separation 19

The improvement of change detection from multi-date satellit...

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IEEE 19th Mediterranean Microwave Symposium (MMS)

作者： Echtioui, Amira Ben Sassi, Olfa Sellami, Lamia Ben Hamida, Ahmed Natl Sch Engn Sfax Adv Technol Med & Signals Sfax Tunisia Higher Inst Comp Sci Adv Technol Med & Signals Tunis El Manar Tunisia Higher Inst Biotechnol Sfax Adv Technol Med & Signals Sfax Tunisia

ISBN: (纸本)9781728140643

The development of satellites with the strong temporal repetitiveness and development of remote sensing techniques resulted in the advancement of change detection techniques from geospatial imagery. The natural events cause many modifications in the control process of the ecosystems. There is a necessity of using a method capable to map, categorize and monitor areas affected by natural events along time. In this article, a novel methodology of change detection is proposed in order to improve the change detection from multi-date satellite image using the source separation. The results obtained by our methodology are efficient and effective.

关键词： change detection source separation jade algorithm SOBI algorithm EM algorithm classification Post-classification multi-date image

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Fast ICA and jade algorithms for DS-CDMA 2

Fast ICA and JADE Algorithms for DS-CDMA

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2nd Al-Sadiq International Conference on Multidisciplinary in IT and Communication Science and Applications (AIC-MITCSA)

作者： Sadkhan, Sattar B. Mohammed, Samir J. Shubbar, Mafaz M. Univ Babylon IT Coll Hillah Iraq Univ Babylon Engn Coll Hillah Iraq

ISBN: (纸本)9781538642412

This paper introduces application of Independent Component Analysis (ICA) in communication field for Direct Sequence Code Division Multiple Access (DS-CDMA) in symbol estimation, where ICA is statistical method for source separation based on independence between sources, and the paper developed a way to solve the ambiguities of ICA. We used ICA as a detector and it is simulated using MATLAB in downlink DS-CDMA. Fast ICA and jade algorithms which are ICA algorithms are introduced for symbol detection for different number of users and different number of symbols. A comparison between the two algorithms is also made, the results are compared with results of conventional detection. The results showed that ICA detection can solve symbol detection. The ICA detection after solving ambiguities using the proposed way gives better results than conventional detection

关键词： ICA DS-CDMA jade algorithm Fast ICA

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An unsupervised method to determine the optimal number of independent components

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EXPERT SYSTEMS WITH APPLICATIONS 2017年 75卷 56-62页

作者： Mur, Angel Dormido, Raquel Duro, Natividad Mercader, Daniel UNED Dept Comp Sci & Automat Control Juan Rosal 16 Madrid 28040 Spain

In this paper, we present a new method to determine the optimal number of independent components after applying an Independent Component Analysis (ICA) to a set of mixed signals. The proposed method, called Linear Correlations between Components (LCC), uses the jade algorithm to calculate the independent components. The LCC method allows to automatically select the optimal number of independent components in an unsupervised way without any previous knowledge. It has been tested using synthetic mixed signals where the number of pure (or independent) signals is known. This method is very simple, fast and easy to implement. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Distance correlation ICA jade algorithm Linear correlation Optimal number of independent components

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Non-contact cardiac pulse rate estimation based on web-camera 6

Non-contact cardiac pulse rate estimation based on web-camer...

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6th International Conference on Electronics and Information Engineering (ICEIE)

作者： Wang, Yingzhi Han, Tailin Changchun Univ Sci & Technol Changchun 130022 Peoples R China

ISBN: (纸本)9781510600294

In this paper, we introduce a new methodology of non-contact cardiac pulse rate estimation based on the imaging Photoplethysmography (iPPG) and blind source separation. This novel's approach can be applied to color video recordings of the human face and is based on automatic face tracking along with blind source separation of the color channels into RGB three-channel component. First of all, we should do some pre-processings of the data which can be got from color video such as normalization and sphering. We can use spectrum analysis to estimate the cardiac pulse rate by Independent Component Analysis (ICA) and jade algorithm. With Bland-Altman and correlation analysis, we compared the cardiac pulse rate extracted from videos recorded by a basic webcam to a Commercial pulse oximetry sensors and achieved high accuracy and correlation. Root mean square error for the estimated results is 2.06bpm, which indicates that the algorithm can realize the non-contact measurements of cardiac pulse rate.

关键词： facial imaging jade algorithm cardiac pulse rate non-contact measurement

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Separation of source signals from multichannel ultrasonic measurements on concrete

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TM-TECHNISCHES MESSEN 2015年第9期82卷 432-439页

作者： Feller, Viktor Orglmeister, Reinhold Mielentz, Frank TU Berlin Sekretariat EN3 D-10587 Berlin Germany BAM Fachbereich Zerstorungsfreie Schadensdiag & Umwel D-12200 Berlin Germany

This work presents the latest advances in ultrasonic testing of concrete structures based on the independent component analysis (ICA) method. This approach has already been successfully applied in other areas of ultrasonic testing. Its advantage when compared to other methods is the possibility to separate overlapping ultrasonic returns from closely spaced reflectors by analyzing only few measurements in real time and to locate reflectors using simple triangulation. Experiments were carried out to analyze the efficiency and practical relevance of the jade algorithm. Investigations were performed on polyamide and concrete test objects. The performance of the jade algorithm is evaluated by the quality of separation of multi-channel ultrasonic measurements. The extracted components include signal parts which correlate with the corresponding echo signals in the measurement. Further investigations are planned where the ICA method in combination with the phased array beamforming technique and a suitable transmitter-receiver concept will be used to increase the information gained during ultrasonic non-destructive testing.

关键词： Blind source separation (BSS) independent component analysis (ICA) jade algorithm ultrasound

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A Novel Implementation of Double Precision and Real Valued ICA algorithm for Bioinformatics Applications on GPUs

A Novel Implementation of Double Precision and Real Valued I...

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18th International Conference on Euro-Par Parallel Processing

作者： Foshati, Amin Khunjush, Farshad Shiraz Univ Dept Comp Sci & Engn Int Div Shiraz Iran Hormozgan Univ Dept Elect Engn Bandar Abbas Iran Shiraz Univ Sch Elect & Comp Engn Dept Comp Sci & Engn Shiraz Iran IPM Inst Res Fundamental Sci Sch Comp Sci Tehran Iran

ISBN: (纸本)9783642369490

Several applications in the field of bioinformatics require extracting individual source signals from a large amount of observed data (signal mixtures). Among the available solutions, a possible approach is the independent component analysis (ICA). However, this computationally intensive algorithm does not fit for many real-time or large size data applications. As a result, this shortcoming calls for speeding up the execution of this algorithm. Recently, graphics processing units (GPUs) have emerged as general-purpose parallel processing accelerators. This platform has the potentials to be leveraged in processing a large amount of signals received from medical devices such as EEG and ECG tools. This work provides the implementation of an ICA algorithm, Joint Approximate Diagonalization of Eigen-matrices (jade), on a low cost programmable graphics cards using CUDA programming toolkits. For this implementation, we achieved an overall speedup of over 7.9x for estimating 64 components, each with 9760 samples.

关键词： Independent Component Analysis (ICA) jade algorithm Blind Source Separation (BSS) Graphics Processing Units (GPUs) CUDA Bioinformatics Applications

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