Recursive Sine Cosine Base Function Neural Network for Proximity Capacitive Gesture Recognition

摘要

This paper presented a recursive sine cosine base function neural network (RSCNN) user gesture base on proximity capacitive sensor. The human interactive gesture signal analyses have been a research topic smart home fields that algorithms build in local device to recognize real time. The neural network have been used in many fields that including identification, control and classification. RSCNN features is used sine and cosine base function to map input signal which have wide range function to receive uncertainty input signal range. Moreover, the recursive weight record previous signal to add learn procession. Therefore, the RSCNN methods to identify user gesture has satisfactory response.