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11.
Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia. 相似文献
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The paper focuses on the adaptive relational association rule mining problem. Relational association rules represent a particular type of association rules which describe frequent relations that occur between the features characterizing the instances within a data set. We aim at re-mining an object set, previously mined, when the feature set characterizing the objects increases. An adaptive relational association rule method, based on the discovery of interesting relational association rules, is proposed. This method, called ARARM (Adaptive Relational Association Rule Mining) adapts the set of rules that was established by mining the data before the feature set changed, preserving the completeness. We aim to reach the result more efficiently than running the mining algorithm again from scratch on the feature-extended object set. Experiments testing the method's performance on several case studies are also reported. The obtained results highlight the efficiency of the ARARM method and confirm the potential of our proposal. 相似文献
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Ratnabali Biswas Kaushik Chowdhury Dharma P. Agrawal 《International Journal of Wireless Information Networks》2006,13(4):303-315
Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes. 相似文献
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WCDMA作为第三代移动通信系统的主流标准,能够提供多种类型的多媒体服务。为了实现各种用户平面数据的传输,系统会提前通过控制平面对所需的无线资源进行分配。由于配置过程是通过接口之间发送控制平面应用协议消息来实现的,因此能否正确有效地对信令消息进行编解码成为保证系统稳定工作的关键因素。3GPP标准中,ASN.1语言被用来描述接口信令消息。首先简要介绍了WCDMA系统结构以及主要接口协议,重点描述了ASN.1存在的意义及其编解码规则,最后给出了基于ASN.1的开发环境下应用层网络协议的开发流程。 相似文献
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ZhaoYahong ZhangZhongpei WuWeiling 《电子科学学刊(英文版)》2003,20(3):177-182
Adaptive modulation and power allocation is introduced into the multicarrier DSCDMA system to improve the system performance and bandwidth efficiency.First,the system design appropriate for adaptive modulation and power allocation is given,then the algorithm of adaptive modulation and power allocation is applied.Simulation results demonstrate great performance improvement compared with the fixed modulated one. 相似文献
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I. Tsukanov M. Hall 《International journal for numerical methods in engineering》2003,56(13):1949-1972
In this paper we discuss the data structure and algorithms for the direct application of generalized Leibnitz rules to the numerical computation of partial derivatives in forward mode. The proposed data structure provides constant time access to the partial derivatives, which accelerates the automatic differentiation computations. The interaction among elements of the data structure is explained by several numerical examples. The paper contains analysis of the developed data structure and algorithms. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
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自适应阵对角线加载研究 总被引:5,自引:0,他引:5
本文分析了对角线加载对自适应阵性能的影响,提出了加载门限的概念,以及加载门限的计算公式,为加载量的选取提供了方法和依据,并将加载研究的结果加以推广,提出了有效的LS自适应波束形成算法的非零初始化方法。 相似文献