Localization for Wireless Sensor Networks with Improved Dv-Hop and Spring-Model Refinement

The sensor node positioning is the important technology in Wireless Sensor Network. DV-Hop algorithm has the accumulative errors during the sensor positioning procedure. In order to increase the DV-Hop positioning precisions this paper first corrects the distance of the average hop in DV-Hop algorithm, then introduces cuckoo searching algorithm to optimize the sensor node positioning errors, and finally applies simulation experiment to test the performance. The simulation experiment illustrates the proposed algorithm needs extra hardware support in order to increase the Sensor positioning precisions compared to DV-Hop algorithm. Even with fewer anchor nodes,the proposed algorithm can obtain ideal positioning results with high practical value.

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Research on Wavelet Transform Method Based on SURF Threshold Improved Mallat

Yuan¹,

Huang²

2014

TOAUTOCJ

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In this paper, watant role in the signal processing. Analyzing the limitations of Fourier transform in the signal processing, this article reflects the superiority of the wavelet transform, analyzes the principle of Mallat wavelet transform, builds decomposition and reconstruction model of Mallat wavelet, and introduces the SURF threshold to improve Mallat transform method. Finally, comparing the denoising results of single Mallat and improved Mallat, the paper verifies that the improved Mallat method is feasible.

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Localization for Wireless Sensor Networks with Improved Dv-Hop and Spring-Model Refinement

Cited by 3 publications

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Secure and Robust DV-Hop Localization Based on the Vector Refinement Feedback Method for Wireless Sensor Networks

Secure and Robust DV-Hop Localization Based on the Vector Refinement Feedback Method for Wireless Sensor Networks

The research on Wireless Sensor Network node positioning based on DV-hop algorithm and cuckoo searching algorithm

Research on Wavelet Transform Method Based on SURF Threshold Improved Mallat

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