ANFIS-Based Signal Reconstruction for Nonlinear Multifunctional Sensor
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In this paper, one approach based on adaptive network-based fuzzy inference system is designed to reconstruct signal for nonlinear multifunctional sensor used in multifunctional sensing technique. Before training, fuzzy rule number is automatically obtained through subtractive clustering to simplify the model structure. Simulation results for an analog circuit model which simulates a nonlinear multifunctional sensor system demonstrate the effectiveness of the designed approach in reconstructing signal. Application of processing real-life data reveals performance of the proposed method is evidently promoted by combining with fuzzy c-means clustering.
KeywordsMultifunctional sensing Signal reconstruction Nonlinearity ANFIS Subtractive clustering
The authors thank Prof. Guo Wei, Harbin Institute of Technology, for providing the real-life multifunctional sensor data.
This work is supported in part by the National Natural Science Foundation of China (61201364) and the Fundamental Research Funds for the Central Universities (NS2016034).
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