Further Results on the Distinctness of Decimations of l-sequences

Let $\underline{a}$ be an \textit{l}-sequence generated by a feedback-with-carry shift register with connection integer $q=p^{e}$, where $p$ is an odd prime and $e\geq 1$. Goresky and Klapper conjectured that when $p^{e}\notin \{5,9,11,13\}$, all decimations of $\underline{a}$ are cyclically distinct. When $e=1$ and $p>13$, they showed that the set of distinct decimations is large and, in some cases, all deciamtions are distinct. In this article, we further show that when $e\geq 2$ and$p^{e}\neq 9$, all decimations of $\underline{a}$ are also cyclically distinct.Comment: submitted to IEEE-I

Multi-view Vector-valued Manifold Regularization for Multi-label Image Classification

In computer vision, image datasets used for classification are naturally associated with multiple labels and comprised of multiple views, because each image may contain several objects (e.g. pedestrian, bicycle and tree) and is properly characterized by multiple visual features (e.g. color, texture and shape). Currently available tools ignore either the label relationship or the view complementary. Motivated by the success of the vector-valued function that constructs matrix-valued kernels to explore the multi-label structure in the output space, we introduce multi-view vector-valued manifold regularization (MV$\mathbf{^3}$MR) to integrate multiple features. MV$\mathbf{^3}$MR exploits the complementary property of different features and discovers the intrinsic local geometry of the compact support shared by different features under the theme of manifold regularization. We conducted extensive experiments on two challenging, but popular datasets, PASCAL VOC' 07 (VOC) and MIR Flickr (MIR), and validated the effectiveness of the proposed MV$\mathbf{^3}$MR for image classification

Universal role of migration in the evolution of cooperation

We study the role of unbiased migration in cooperation in the framework of spatial evolutionary game on a variety of spatial structures, involving regular lattice, continuous plane and complex networks. A striking finding is that migration plays a universal role in cooperation, regardless of the spatial structures. For high degree of migration, cooperators cannot survive due to the failure of forming cooperator clusters to resist attacks of defectors. While for low degree of migration, cooperation is considerably enhanced compared to statically spatial game, which is due to the strengthening of the boundary of cooperator clusters by the occasionally accumulation of cooperators along the boundary. The cooperator cluster thus becomes more robust than that in static game and defectors nearby the boundary can be assimilated by cooperators, so the cooperator cluster expands, which facilitates cooperation. The general role of migration will be substantiated by sufficient simulations associated with heuristic explanations.Comment: 5 pages, 4 figure

Emergence of cooperation induced by preferential learning

The evolutionary Prisoner's Dilemma Game (PDG) and the Snowdrift Game (SG) with preferential learning mechanism are studied in the Barab\'asi-Albert network. Simulation results demonstrate that the preferential learning of individuals remarkably promotes the cooperative behavior for both two games over a wide range of payoffs. To understand the effect of preferential learning on the evolution of the systems, we investigate the time series of the cooperator density for different preferential strength and payoffs. It is found that in some specific cases two games both show the $1/f$-scaling behaviors, which indicate the existence of long range correlation. We also figure out that when the large degree nodes have high probability to be selected, the PDG displays a punctuated equilibrium-type behavior. On the contrary, the SG exhibits a sudden increase feature. These temporary instable behaviors are ascribed to the strategy shift of the large degree nodes.Comment: 10 pages, 5 figure

Compressed Sensing SAR Imaging with Multilook Processing

Multilook processing is a widely used speckle reduction approach in synthetic aperture radar (SAR) imaging. Conventionally, it is achieved by incoherently summing of some independent low-resolution images formulated from overlapping subbands of the SAR signal. However, in the context of compressive sensing (CS) SAR imaging, where the samples are collected at sub-Nyquist rate, the data spectrum is highly aliased that hinders the direct application of the existing multilook techniques. In this letter, we propose a new CS-SAR imaging method that can realize multilook processing simultaneously during image reconstruction. The main idea is to replace the SAR observation matrix by the inverse of multilook procedures, which is then combined with random sampling matrix to yield a multilook CS-SAR observation model. Then a joint sparse regularization model, considering pixel dependency of subimages, is derived to form multilook images. The suggested SAR imaging method can not only reconstruct sparse scene efficiently below Nyquist rate, but is also able to achieve a comparable reduction of speckles during reconstruction. Simulation results are finally provided to demonstrate the effectiveness of the proposed method.Comment: Will be submitted to GRS lette

Dynamical Coarse Graining of Large Scale-Free Boolean networks

We present a renormalization-grouplike method performed in the state space for detecting the dynamical behaviors of large scale-free Boolean networks, especially for the chaotic regime as well as the edge of chaos. Numerical simulations with different coarse-graining level show that the state space networks of scale-free Boolean networks follow universal power-law distributions of in and out strength, in and out degree, as well as weight. These interesting results indicate scale-free Boolean networks still possess self-organized mechanism near the edge of chaos in the chaotic regime. The number of state nodes as a function of biased parameter for distinct coarse-graining level also demonstrates that the power-law behaviors are not the artifact of coarse-graining procedure. Our work may also shed some light on the investigation of brain dynamics.Comment: 5 pages, 6 figure

Diffusion-limited-aggregation on a directed small world network

For real world systems, nonuniform medium is ubiquitous. Therefore, we investigate the diffusion-limited-aggregation process on a two dimensional directed small-world network instead of regular lattice. The network structure is established by rewiring connections on the two dimensional directed lattice. Those rewired edges are controlled by two parameters $\theta$ and $m$, which characterize the spatial length and the density of the long-range connections, respectively. Simulations show that there exists a maximum value of the fractal dimension when $\theta$ equals zero. Interestingly, we find that the symmetry of the aggregation pattern is broken when rewired connections are long enough, which may be an explanation for the formation of asymmetrical fractal in nature. Then, we perform multifractal analysis on the patterns further.Comment: 5 pages, 5 figure

Fast Compressed Sensing SAR Imaging based on Approximated Observation

In recent years, compressed sensing (CS) has been applied in the field of synthetic aperture radar (SAR) imaging and shows great potential. The existing models are, however, based on application of the sensing matrix acquired by the exact observation functions. As a result, the corresponding reconstruction algorithms are much more time consuming than traditional matched filter (MF) based focusing methods, especially in high resolution and wide swath systems. In this paper, we formulate a new CS-SAR imaging model based on the use of the approximated SAR observation deducted from the inverse of focusing procedures. We incorporate CS and MF within an sparse regularization framework that is then solved by a fast iterative thresholding algorithm. The proposed model forms a new CS-SAR imaging method that can be applied to high-quality and high-resolution imaging under sub-Nyquist rate sampling, while saving the computational cost substantially both in time and memory. Simulations and real SAR data applications support that the proposed method can perform SAR imaging effectively and efficiently under Nyquist rate, especially for large scale applications.Comment: Submitted To IEEE-JSTA

Optimization parameter design for proton irradiation accelerator

The proton irradiation accelerator is widely founded for industry application, and should be designed as compact, reliable, and easy operate. A 10 MeV proton beam is designed to be injected into the slow circulation ring with the repetition rate of 0.5 Hz for accumulation and acceleration, and then the beam with the energy of 300MeV will be slowly extracted by third order resonance method. For getting a higher intensity and more uniform beam, the height of the injection bump is carefully optimised during the injection period. Besides, in order to make the extracted beam with a more uniform distribution, a RF Knock-out method is adopted, and the RF kicker's amplitude is well optimised

Nuclear constraints on the core-crust transition density and pressure of neutron stars

Using the equation of state of asymmetric nuclear matter that has been recently constrained by the isospin diffusion data from intermediate-energy heavy ion collisions, we have studied the transition density and pressure at the inner edge of neutron star crusts, and they are found to be 0.040 fm^{-3} <= \rho_{t}<= 0.065 fm^{-3} and 0.01 MeV/fm^{3} <= P_{t} <= 0.26 MeV/fm^{3}, respectively, in both the dynamical and thermodynamical approaches. We have further found that the widely used parabolic approximation to the equation of state of asymmetric nuclear matter gives significantly higher values of core-crust transition density and pressure, especially for stiff symmetry energies. With these newly determined transition density and pressure, we have obtained an improved relation between the mass and radius of neutron stars based on the observed minimum crustal fraction of the total moment of inertia for Vela pulsar.Comment: 9 pages, 3 figures. Contribution to Compact stars in the QCD phase diagram II (CSQCD II), May 20-24, 2009, Beijing, Chin