Notice of RetractionAn enhanced streaming pattern discovery algorithm for sensor networks

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

This paper proposes an enhanced pattern discovery algorithm for data streams processing of sensor networks, in order to improve the performance of SPIRIT. The new algorithm adapts the optimized correction for tracking weights vectors, and the dynamic expanding in detecting the number of hidden variables. Simulation results show that compared to the original algorithm, the proposed algorithm can reduce the reconstruction error, increase the energy fraction of reconstruction, and decrease the number of hidden variables, so it extract the principal components and discover patterns among streams more efficiently.