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This paper describes the role of algorithm development in the IEEE standard 21451.001. The purpose is to promote and enhance the computational capabilities of smart transducers and facilitate the flow from sensor raw data processing to sensor knowledge fusion. A case study on real-time segmentation and labeling is conducted to demonstrate the feasibility of the first layer algorithm. The key role...
Outlier detection is an important issue in data mining and knowledge discovery. The aim is to find the patterns that deviate too much from others. In this paper, a universal outlier detection method based on normalized residual is proposed. Different from previous methods, the residual of a pattern is calculated corresponding to its nearest normal patterns, so that the interaction between outliers...
With a growing amount of data, a viable solution is to use a cluster consisting of a large of computers for parallel processing, and Hadoop parallel computing platform is a typical representative. Clustering analysis for time series data is one of the main methods mining time series data, however, general clustering algorithms can't perform clustering for time series data directly since series data...
One of the main problems facing beamforming in array system is impulse noise. Although traditional Minimum Variance Distortionless Response (MVDR) beamformer [1] based on classical techniques under minimizing a least-squares objective function has the optimum capabilities of signal protection, interference removal and noise reduction in Gaussian noise environment, it loses optimality when the noise...
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