An optimal algorithm for computing the max–min transitive closure of a fuzzy similarity matrix

2001 ◽  
Vol 123 (1) ◽  
pp. 129-136 ◽  
Author(s):  
Hsuan-Shih Lee
Author(s):  
Subhanshu Goyal ◽  
Sushil Kumar ◽  
M. A. Zaveri ◽  
A. K. Shukla

In recent times, graph based spectral clustering algorithms have received immense attention in many areas like, data mining, object recognition, image analysis and processing. The commonly used similarity measure in the clustering algorithms is the Gaussian kernel function which uses sensitive scaling parameter and when applied to the segmentation of noise contaminated images leads to unsatisfactory performance because of neglecting the spatial pixel information. The present work introduces a novel framework for spectral clustering which embodied local spatial information and fuzzy based similarity measure to tackle the above mentioned issues. In our approach, firstly we filter the noise components from original image by using the spatial and gray–level information. The similarity matrix is then constructed by employing a similarity measure which takes into account the fuzzy c-partition matrix and vectors of the cluster centers obtained by fuzzy c-means clustering algorithm. In the last step, spectral clustering technique is realized on derived similarity matrix to obtain the desired segmentation result. Experimental results on segmentation of synthetic and Berkeley benchmark images with noise demonstrates the effectiveness and robustness of the proposed method, giving it an edge over the clustering based segmentation method reported in the literature.


2020 ◽  
Vol 28 (4) ◽  
pp. 157-173
Author(s):  
Jie Zhao ◽  
Rikun Wen ◽  
Wen Mei

Taking garden heritage ontologies as the object, this paper explores monitoring and early-warning methods of heritage based on fuzzy cluster analysis. A monitoring and early-warning system for garden heritage ontologies is designed and consists of monitoring indexes, a monitoring program, monitoring data collection, application of an early-warning grading evaluation model and conclusion of early-warning grading. Taking the Suzhou classical garden heritage as an example, it can be concluded that the systematic method can integrate various qualitative and quantitative index values and collectively reflect the overall state of garden heritage ontologies as well as match a heritage monitoring ontology with an early warning grade by calculating the data similarity matrix, membership matrix, fuzzy similarity matrix, fuzzy equivalent matrix and cut matrix. Five kinds of heritage ontologies with a total of twenty-seven heritage monitoring indicators are applied in the model and then be matched with MATLAB software to obtain accurate early-warning results. When types of heritage ontology need to be expanded, the heritage is further refined, or the heritage is more comprehensive, this method is applicable.


2013 ◽  
Vol 295-298 ◽  
pp. 882-887
Author(s):  
Jian Jin ◽  
Jing Chao Hu

31 of China’s provinces was divided into seven categories by a process of collecting data, standardizing data, creating fuzzy similarity matrix and fuzzy equivalent matrix, and finding the threshold value. There is not strictly positive correlation between environmental pollution and economic growth in China’s provinces. Because of different industry development policy and industry feature, environmental pollution in some more developed provinces and cities is less serious, while that in some provinces of the intermediate level is more serious.


2011 ◽  
Vol 228-229 ◽  
pp. 179-184
Author(s):  
Jing Jiang ◽  
Lan Shu ◽  
Xin An Tian

Since the transitive closure of a lattice matrix can be used to analyze the maximum road of network of traffic control and logistics, the study of the transitive closure of a lattice matrix is valua- ble. A matrix is called a lattice matrix if its elements belong to a distributive lattice. In this paper, the transitivity of powers and the closure of a lattice matrix are studied. Also, an optimal algorithm for co- mputing the transitive closure of a lattice matrix is posed.


Author(s):  
Алексей Дмитриевич Акишин ◽  
Иван Павлович Семчук ◽  
Александр Петрович Николаев

Постоянно растущий интерес к разработке новых неинвазивных и безманжетных методов измерения параметров сердечной деятельности, использование которых давало бы возможность непрерывного и удаленного контроля сердечно-сосудистой системы, обуславливает актуальность данной работы. В многочисленных публикациях продолжаются обсуждения преимуществ и недостатков различных методов ранней диагностики сердечно-сосудистых заболеваний. Однако артефакты движения являются сильной помехой, мешающей точной оценке показателей функционирования сердечно-сосудистой системы. Одним из перспективных методов контроля является метод оценки физиологических параметров с использованием фотоплетизмографии. Данная статья посвящена разработке устройства для фотоплетизмографических исследований и алгоритмических методов обработки регистрируемых сигналов для обеспечения мониторинга сердечного ритма с заданной точностью. В работе используются технологии цифровой адаптивной фильтрации полученных сигналов для мониторинга сердечного ритма в условиях внешних механических и электрических помеховых воздействий, ухудшающих точностные характеристики системы, а также разработана архитектура системы и изготовлен макет устройства, который позволил провести измерения для определения оптимального алгоритма цифровой обработки сигналов. При использовании устройства применялись методы адаптивной фильтрации на основе фильтров Винера, фильтров на основе метода наименьших квадратов и Калмановской фильтрации. Разработанное устройство для фотоплетизмографических исследований обеспечило возможность мониторинга сердечного ритма с заданной точностью, контроля текущего состояния организма и может быть использовано в качестве средства диагностики заболеваний сердца The constantly growing interest in the development of new non-invasive and cuff-free methods for measuring the parameters of cardiac activity, the use of which would give the possibility of continuous and remote monitoring of the cardiovascular system, determines the relevance of this work. Numerous publications continue to discuss the advantages and disadvantages of various methods of early diagnosis of cardiovascular disease. However, motion artifacts are a strong hindrance to the accurate assessment of the performance of the cardiovascular system. One of the promising control methods is the method for assessing physiological parameters using photoplethysmography. This article is devoted to the development of a device for photoplethysmographic studies and algorithmic methods for processing recorded signals to ensure monitoring of the heart rate with a given accuracy. The work uses technologies of digital adaptive filtering of the received signals to monitor the heart rate in conditions of external mechanical and electrical interference, which worsen the accuracy characteristics of the system, as well as the architecture of the system and a prototype of the device, which made it possible to carry out measurements to determine the optimal algorithm for digital signal processing. When using the device, the methods of adaptive filtering based on Wiener filters, filters based on the least squares method and Kalman filtering were used. The developed device for photoplethysmographic studies provided the ability to monitor the heart rate with a given accuracy, control the current state of the body and can be used as a means of diagnosing heart diseases


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