A clustering algorithm based on Sparse Projection (SP), called Sparse Projection Clus- tering (SPC), is proposed in this letter. The basic idea is applying SP to project the observed data onto a high-dimensional sparse space, which is a nonlinear mapping with an explicit form and the K-means clustering algorithm can be therefore used to explore the inherent data patterns in the new space. The proposed algorithm is applied to cluster a complete artificial dataset and an incomplete real dataset. In comparison with the kernel K-means clustering algorithm, the proposed algorithm is more efficient.
The optical chaotic communication system using open-loop fiber transmission is studied under strong injection conditions. The optical chaotic communication system with open-loop configuration is studied using fiber transmission under strong injection conditions. The performances of fiber links composed of two types of fiber segments in different dispersion compensation maps are compared by testing the quality of the recovered message with different bit rates and encrypted by chaotic modulation (CM) or chaotic shift keying (CSK). The result indicates that the performance of the pre-compensation map is always worst. Two types of symmetrical maps are identical whatever the encryption method and bit-rate of message are. For the transmitting and the recovering of message of lower bit rate (1 Gb/s), the post-compensation map is the best scheme. However, for the message of higher bit rate (2.5 Gb/s), the parameters in communication system need to be modified properly in order to adapt to the high-speed application. Meanwhile, two types of symmetrical maps are the best scheme. In addition, the CM method is superior to the CSK method for high-speed applications. It is in accordance with the result in a back-to-back configuration system.
This paper proposes a denoising algorithm called truncated sparse decomposition (TSD) algorithm, which combines the advantage of the sparse decomposition with that of the minimum energy model truncation operation. Experimental results on two real chaotic signals show that the TSD algorithm outperforms the recently reported denoising algorithmsnon-negative sparse coding and singular value decomposition based method.
A new image coding approach is proposed by controlling the quantization step via minimizing the perceptual distortions(in terms of image's contrast measurement).The proposed method is a rate-oriented contrast-based approach,which is in contrast to the conventional quality-oriented contrast-based image coding.The algorithm achieves a higher perceptual quality performance against several methods developed previously.