An advanced source number estimation (SNE) algorithm based on both fuzzy C-means clustering (FCM) and data local density (DLD) is proposed in this paper. The DLD of an eigenvalue refers to the number of eigenvalues within a specific neighborhood of this eigenvalue belonging to the data covariance matrix. This local density essentially as the one-dimensional sample feature of the FCM is extracted into the SNE algorithm based on FCM and can enable to improve the probability of correct detection (PCD) of the SNE algorithm based on the FCM especially for low signal-to-noise ratio (SNR) environment. Comparison experiment results demonstrate that compared to the SNE algorithm based on the FCM and other similar algorithms, our proposed algorithm can achieve highest PCD of the incident source number in both cases of spatial white noise and spatial correlation noise.
Aiming at the problems of the WPKI certificate verification schemes based on online certificate status protocol (OCSP), this paper proposes a WPKI certificate verification scheme based on the certificate digest signature-online certificate status protocol (CDS OCSP). Compared with the existing schemes, the proposed scheme optimizes the number of communication connections between the communication entities and the network, reduces the consumption of the wireless network bandwidth in the certificate verification process, and uses the elliptic curves cipher-(ECC-) based encrypting/decrypting functions to sign and verify the certificate digest, which ensures the consistency of the verified certificates among the communication entities. The proposed scheme makes the certificate verification process more efficient and secure. The experimental results show that the proposed scheme effectively reduces the communication consumption of the wireless network and saves the storage space of the wireless entities.
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