In this work, an ultra-wideband and high-efficiency reflective linear-to-circular polarization converter based on an anisotropic metasurface is proposed, which is an orthotropic structure with a pair of mutually perpendicular symmetric axes $u$ and $v$ along ±45° directions with respect to the vertical $y$ axis. The simulated and experimental results show that the polarization converter can realize ultra-wideband linear-to-circular polarization conversion at both $x$ - and $y$ -polarized incidences, its 3dB-axial-ratio-band is between 5.8 and 20.4 GHz, which is corresponding to a relative bandwidth of 112%; moreover, the polarization conversion efficiency (PCE) can be kept larger than 99.6% in the frequency range of 6.1–19.8GHz. In addition, to get an insight into the root cause of the LTC polarization conversion, a detailed theoretical analysis is presented, in which the conclusion is reached that in the case of neglecting thelittle dielectric loss, the axial ratio (AR) of the reflected wave can be completely determined by the phase difference between the two reflection coefficients at $u$ - and $v$ -polarized incidences, and any anisotropic metasurface can be used as an effective LTC polarization converter when the phase difference is close to ±90°.
In the communication, a monopolarized and a dual-polarized polarization-rotating frequency-selective surfaces (PR-FSSs) are designed successively. The two PR-FSSs are both a three-layer aperture-coupled-patch periodic structure. When they are interpreted as an array of antenna-filter-antenna (AFA) modules, because polarization directions of the upper and lower antennas in each AFA module are orthogonal to each other, they can both realize polarization rotation and frequency selection at the same time. The monopolarized PR-FSS is designed first, its relative bandwidth reaches up to 13.58% although there is a maximum insertion loss of 0.8 dB in the band. The final-designed dual-polarized PR-FSS can be regarded as the combination of two orthogonal monopolarized one, so it can work under both $x$ - and $y$ -polarized incidences, its relative bandwidth is still up to 9.81%; moreover, the maximum insertion loss in the passband is very low. The performances of the two PR-FSSs are both verified by simulations and experiments.
HITS algorithm is a famous topic distillation algorithm, but it has a drawback of topic drift. To tackle this problem, a new improved HITS algorithm is proposed by assigning appropriate weights to links according to the link value and topic similarity. Based on an analysis of web link structure, link value is calculated by web page authority degree; topic similarity of web pages is calculated by combining analysis of page content with HTML structure characteristics. Improved HITS algorithm combining link value with topic similarity highlights the difference of links and it assigns different weights to different links. Experiment results indicate that the proposed HITS algorithm can improve the relevance ratio by 13%-42%. Furthermore it can well control topic drift and enhance the accuracy of information collection. The proposed HITS algorithm can be applied in vertical search engines. It lays an important theoretical foundation for vertical search engines.
Though several algorithms inspired by theoretical immunology have been applied to the domain of pattern classification, little focus has been placed on the issues that simultaneously optimize more than one objective-functions.Here, an efficient multi-objective automatic segmentation framework (MASF) is formulated and applied to SAR image unsupervised classification.In the framework, four important issues are presented: 1) two reasonable image preprocessing techniques are discussed at the initial stage; 2)then, an efficient immune multiobjective optimization algorithm is proposed; 3) besides, a locusbased adjacency representation in individual encoding is introduced; 4) two very simple, but very efficient conflicting clustering validity indices are incorporated into the framework and simultaneously optimized.Both simulated data and real images are used to quantitatively validate its effectiveness.In addition, four other state-of-the-art image segmentation methods are employed for comparison.Experimental results show that the proposed framework is efficient and effective for SAR image segmentation.
Abstract To fully analyze the features extracting from multi-color space for rock classification, each feature will be evaluated in this paper. And, to enhance correlation between features and reduce dimensionality of feature space, a PCA approach will be used and the result of PCA will also be fully analyzed. A C-SVM model is chosen to test analysis result. Data set consist of 500 images from Ordos basin. The classification result between single color space and multi-color space will be compared, and the cooperation result shows that features from multi-color space can support classifier like C-SVM to take higher accuracy and higher reliability.
With the rapid and bursting development of communication engineering and some related techniques, spread spectrum communication and sparse analysis have been a hot research topic in the research community. A novel anti-jamming driven sparse analysis-based spread spectrum communication methodology is proposed in this paper, which mainly increases the spread spectrum modulation and the spread spectrum demodulation in the receiving end. The process of spread spectrum communication according to the working methods of different methodologies including direct-sequence spread spectrum. In this paper, the sparse presentation, dictionary learning, anti-jamming analysis and the basic communication theories are integrated altogether to enhance the traditional spread spectrum communication analysis framework. The experimental result proves the robustness of the proposed method.
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