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Xiaolong ZHENG Bangjie LI Daqiao ZHANG Di YAO Xuguang YANG
High Frequency Surface Wave Radar holds significant potential in sea detection. However, the target signals are often surpassed by substantial sea clutter and ionospheric clutter, making it crucial to address clutter suppression and extract weak target signals amidst the strong noise background.This study proposes a novel method for separating weak harmonic target signals based on local tangent space, leveraging the chaotic feature of ionospheric clutter.The effectiveness of this approach is demonstrated through the analysis of measured data, thereby validating its practicality and potential for real-world applications.
Hidetoshi TANAKA Shigeo SATO Koji NAKAJIMA
A chaotic noise is one of the most important implements for information processing such as neural networks. It has been suggested that chaotic neural networks have high performance ability for information processing. In this paper, we report two designs of a compact chaotic noise generator for large integration circuits using CMOS technology. The chaotic noise is generated using map chaos. We design both of the logistic map type and the tent map type circuits. These chaotic noise generators are compact as compared with the other circuits. The results show that the successful chaotic operations of the circuits because of the positive Lyapunov number. We calculate the Lyapunov exponents to certify the results of the chaotic operations. However, it is hard to estimate its accurate number for noisy data using the conventional method. And hence, we propose the modified calculation of the Lyapunov exponent for noisy data. These two circuits are expected to be utilized for various applications.