Abstract：To measure the similarity between the fine features of communication transmitters, an algorithm of individual communication transmitter identification using maximum correntropy based on l2-regularization is put forward. Firstly, the square integral bispectra of the communication transmitter signal is extracted to characterize the individual differences of communication transmitters, and then optimization model using maximum correntropy criterion based on l2-regularization is constructed. Next, the half-quadratic technique is used to transform the nonlinear optimization problem into a weighted linear least squares problem. Finally, the sparse coefficient can be computed by active set algorithm, and then the classifier is constructed by mining the discriminative information of coefficient for the communication transmitters identification. The feasibility and the effectiveness of the proposed algorithm are verified on the real datasets collected from the FM radios with same manufacturer and model.
唐哲，雷迎科. 通信辐射源个体识别中基于l2正则化的最大相关熵算法*[J]. 模式识别与人工智能, 2016, 29(6): 527-533.
TANG Zhe, LEI Yingke. Algorithm of Maximum Correntropy Based on l2-Regularization in Individual Communication Transmitter Identification. , 2016, 29(6): 527-533.
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