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Sequential change-point detection via the Cross-Entropy method 通过交叉熵方法进行序列变化点检测
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6420004
G. Sofronov, T. Polushina, M. Priyadarshana
{"title":"Sequential change-point detection via the Cross-Entropy method","authors":"G. Sofronov, T. Polushina, M. Priyadarshana","doi":"10.1109/NEUREL.2012.6420004","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6420004","url":null,"abstract":"Change-point problems (or break point problems, disorder problems) can be considered one of the central issues of statistics, connecting asymptotic statistical theory and Monte Carlo methods, frequentist and Bayesian approaches, fixed and sequential procedures. In many real applications, observations are taken sequentially over time, or can be ordered with respect to some other criterion. The basic question, therefore, is whether the data obtained are generated by one or by many different probabilistic mechanisms. Change-point problems arise in a wide variety of fields, including biomedical signal processing, speech and image processing, climatology, industry (e.g. fault detection) and financial mathematics. In this paper, we apply the Cross-Entropy method to a sequential change-point problem. We obtain estimates for thresholds in the Shiryaev-Roberts procedure and the CUSUM procedure. We provide examples with generated sequences to illustrate the effectiveness of our approach to the problem.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123813920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Performance of texture descriptors in classification of medical images with outsiders in database 纹理描述符在数据库外来者医学图像分类中的性能
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6420013
A. Avramović, B. Marovic
{"title":"Performance of texture descriptors in classification of medical images with outsiders in database","authors":"A. Avramović, B. Marovic","doi":"10.1109/NEUREL.2012.6420013","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6420013","url":null,"abstract":"During the years image classification gained important significance in practice, especially in the fields of digital radiology, remote sensing, image retrieval, etc. Typical algorithm for image classification contains descriptor extraction phase, learning phase and testing phase. Testing phase calculates accuracy of the classifier based on predetermined set of labelled images. This paper analyse performance of texture descriptors combined with SVMs, in the case when test dataset contains images not belonging to any predetermined class. A robustness of texture descriptors on outsiders is analysed, to see if descriptor is able to separate outsiders in specific class. Medical dataset containing various radiology images is used for testing. It was shown that it is possible to separate images not belonging to any class with cost of decreased performance by few percent.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122586636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Acoustic features determination for regularity articulation quantification of Serbian fricatives 塞尔维亚语摩擦音规则发音量化的声学特征测定
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6420008
D. Furundžić, S. Jovicic, M. Subotić, S. Punišić
{"title":"Acoustic features determination for regularity articulation quantification of Serbian fricatives","authors":"D. Furundžić, S. Jovicic, M. Subotić, S. Punišić","doi":"10.1109/NEUREL.2012.6420008","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6420008","url":null,"abstract":"This paper presents a brief methodology for determination of relevant parameters for automatic articulation regularity quantification of Serbian fricatives pronunciation. Using the known methods and algorithms as well as developing new ones for analysis of phoneme pronunciation process, authors used neural networks as a tool for modeling. Here we present a comparison of fricative articulation quality assessment, based on the different features of the speech signal.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"2007 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127307973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Comparison between acceleration-enhanced adaptive filters and neural network filters for respiratory motion prediction 加速增强自适应滤波器与神经网络滤波器在呼吸运动预测中的比较
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6420003
Ivan Buzurovic, Ke Huang, T. Podder, Yan Yu
{"title":"Comparison between acceleration-enhanced adaptive filters and neural network filters for respiratory motion prediction","authors":"Ivan Buzurovic, Ke Huang, T. Podder, Yan Yu","doi":"10.1109/NEUREL.2012.6420003","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6420003","url":null,"abstract":"The prediction of respiration-induced organ motion is crucial in some applications such as dynamic delivery of radiation dose. In this paper, we have proposed the novel approach to construct an acceleration-enhanced (AE) filter that is comprised of two independent adaptive channels. The filters use the adapted position and adapted acceleration, together with a weight factor to provide prediction for respiratory motion. The proposed AE approach is universal and can be applied to the different filters. The performances of the adaptive normalized least mean square (nLMS) filter, the artificial neural network (ANN) filter, and their AE counterparts were compared for respiratory motion prediction during normal and irregular respiration. The results revealed that the adaptive ANN and nLMS filters were successful to perform predictions for normal and irregular respiration, respectively. AE filters showed more accurate prediction than their conventional counterparts. Implementing the AE approach, it was observed that the AE-ANN filter had the best performance in the prediction of normal respiratory motion, whereas the AE-nLMS filter excelled in the prediction of irregular respiratory motion.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129243850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
WiiMote control: Gaming feedback for motivational training of the arm movements WiiMote控制:游戏反馈，用于手臂运动的动机训练
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6419984
M. Prodanović, M. Kostic, D. Popovic
{"title":"WiiMote control: Gaming feedback for motivational training of the arm movements","authors":"M. Prodanović, M. Kostic, D. Popovic","doi":"10.1109/NEUREL.2012.6419984","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6419984","url":null,"abstract":"In this paper we present the method for WiiMote position control in order to gain motivational feedback in stroke patients who need to train their arm movements. Developed software acts as interface between input system, such as a computer mouse, which patients could use in rehabilitation, and custom made robotized system for controlling of WiiMote. With this software it is possible to transform any therapy prescribed movements into controls of WiiMote, so Nintendo Wii game could be played successfully.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124660545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Authorship attribution using committee machines with k-nearest neighbors rated voting 作者归属使用委员会机器与k近邻评级投票
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6419997
A. Kuşakcı
{"title":"Authorship attribution using committee machines with k-nearest neighbors rated voting","authors":"A. Kuşakcı","doi":"10.1109/NEUREL.2012.6419997","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6419997","url":null,"abstract":"Authorship attribution, namely determination of the author of a text, may become an extraordinarily complex and sensitive job due to its relatively difficult feature extraction phase and highly nonlinear nature. This paper proposes a classification tool using committee machines consisting of multilayered perceptron neural networks (MLP) to identify the author of a text. Each expert is an individual MLP learning complex input-output relation composed of 14 lexical, stylometric attributes extracted from the corpus. The resulting mapping after training is used to identify the texts in German language written by two different authors. Unlike other committee based classification tools individual answers of the experts are combined with a novel voting method, k-nearest neighbors rated voting. The proposed method shows very promising results when benchmarked with simple majority voting technique.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Cooperative networked systems 协作网络系统
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6419946
S. Stankovic, M. Stankovic
{"title":"Cooperative networked systems","authors":"S. Stankovic, M. Stankovic","doi":"10.1109/NEUREL.2012.6419946","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6419946","url":null,"abstract":"Complexity. Complex systems. Emergence: examples. Swarm intelligence. Ant colony and particle swarm optimization: applications. Stigmergy. Adaptation. Autopoiesis. Multi-agent systems. Graph representation: Laplacian. Flocking: examples from computer, communication, and control sciences. Cooperation in multi agent systems. Decentralized vs. centralized decision making. Networked systems. Cyber-physical systems. Systems of systems.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134343435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PCA sensitivity: The role of representative and outlier strides in gait sequence PCA敏感性:步态序列中代表性步幅和异常步幅的作用
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6419982
V. M. Jerkovic, M. Djuric-Jovicic, M. Popovic
{"title":"PCA sensitivity: The role of representative and outlier strides in gait sequence","authors":"V. M. Jerkovic, M. Djuric-Jovicic, M. Popovic","doi":"10.1109/NEUREL.2012.6419982","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6419982","url":null,"abstract":"Principal component analysis (PCA) is a useful statistical technique for the reduction of data dimensionality. When applied to the accelerometer data in gait analysis PCA assigns common gait patterns among subjects or provides gait classification. In this paper, we study the results of PCA applied to datasets recorded with three-axial accelerometers placed on thigh, shank, and foot in subjects with hemiplegia. In particular, we analyze the impact of both representative stride (the most similar to all other strides in the sequence) and outlier stride (the most different from all other strides in the sequence) on PCA results. PCA sensitivity to data preparation was tested on three datasets: complete gait sequence, gait sequence without the outlier stride, and on representative stride.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133901759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Recognition and classification of deaf signs using neural networks 基于神经网络的聋人手语识别与分类
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6419965
M. Šušić, S. Maksimovic, S. Spasojevic, Z. Durovic
{"title":"Recognition and classification of deaf signs using neural networks","authors":"M. Šušić, S. Maksimovic, S. Spasojevic, Z. Durovic","doi":"10.1109/NEUREL.2012.6419965","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6419965","url":null,"abstract":"One approach for deaf signs recognition and classification is presented in the paper. It is assumed that the signs are presented in digital images. Recognition algorithm is consisted of several stages. At the beginning it is necessary to perform appropriate image processing in sense of segmentation and filtration of the input images. Aim is to detect arm position, i.e. sign of interest. For this purpose classifier for skin detection is used. Next stage has to generate feature vectors, which are used as inputs in neural network. Supervised training of neural network is performed. Reduction algorithm was used for purpose of dimension reduction of feature vectors, so the classification results can be displayed graphically.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114849804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Comparison of neural networks for solving the travelling salesman problem 求解旅行商问题的神经网络比较
11th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2012-09-01 DOI: 10.1109/NEUREL.2012.6419953
B. F. J. La Maire, V. Mladenov
{"title":"Comparison of neural networks for solving the travelling salesman problem","authors":"B. F. J. La Maire, V. Mladenov","doi":"10.1109/NEUREL.2012.6419953","DOIUrl":"https://doi.org/10.1109/NEUREL.2012.6419953","url":null,"abstract":"The TSP deals with finding a shortest path through a number of cities. This seemingly simple problem is hard to solve because of the amount of possible solutions. Which is why methods that give a good suboptimal solution in a reasonable time are generally used. In this paper three methods were compared with respect to quality of solution and ease of finding correct parameters: the Integer Linear Programming method, the Hopfield Neural Network, and the Kohonen Self Organizing Feature Map Neural Network.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"130 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122634269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 23
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