SVM-instance based approach to improve QoS parameters for time critical applications in WSN
SVM-instance based approach to improve QoS parameters for time critical applications in WSN
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DOI：
10.1109/icoac.2012.6416862
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发表时间：
2012-12
期刊：
影响因子：
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通讯作者：
V. Chitra;M. Sumalatha
中科院分区：
文献类型：
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作者：
V. Chitra;M. Sumalatha
QoS因素，如准确性和时间延迟起着重要的作用，在时间关键的应用程序。基于SVM实例的算法提高了紧急车辆声音识别的准确率，减少了识别的时延。在该方法中，通过识别超平面边缘附近的数据点作为支持向量来减少时间延迟，并通过增加类之间的间隔来提高精度。由频率和强度推导出的MFCC用于精确的声音识别。从而减少了识别的时延，提高了识别的准确率。
The QoS factors such as accuracy and time delay plays a major role in time critical applications. The proposed SVM-instance based algorithm improves the accuracy and reduces the time delay for the recognition of emergency vehicle sound. In this approach, the time delay is reduced by identifying the support vectors which are the data points near the margin of hyper plane and the accuracy is increased by increasing the margin between the classes. The MFCC which is derived from frequency and intensity is used for accurate sound recognition. Thus time delay was reduced and accuracy was improved in recognition of emergency vehicle sound.