The link structure of the Web is generally viewed as a webgraph. One of the main objectives of web structure mining is to find hidden communities on the Web based on the webgraph, and one of its approaches tries to enumerate substructures, each of which corresponds to a set of web pages of a community or its core. Research has shown that certain substructures can find sets of pages that are inherently irrelevant to communities. In this paper, we propose a model, which we call contracted webgraphs, where such substructures are contracted into single nodes to hide useless information. We then try structure mining iteratively on those contracted webgraphs since we can expect to find further hidden information once irrelevant information is eliminated. We also explore the structural properties of contracted webgraphs from the viewpoint of scale-freeness, and we observe that they exhibit novel and extreme self-similarities.

This paper describes how to design matching structures to improve the frequency characteristics of one-dimensional finite periodic structures. In particular, it deals with one-dimensional finite superlattices. A downhill simplex method is used to determine some of the structural parameters of the matching structure. Numerical examples show that this method is effective in improving the frequency characteristics of finite superlattices.

After receiving emitted signals from various radars by electronic support measures (ESM) system, several processes are applied to signals such as: deinterleaving, recognition of pulse repetition interval (PRI) modulation, PRI estimation and etc. Indeed, recognition of PRI modulation is an essential task of ESM system. In this paper a novel and robust method for recognition of complicated PRI Modulations is presented. This method uses specifications such as distribution related to members of sequences obtained from first and second order derivation of TOAs around a constant value and continuity of these sequences to recognize the PRI modulation. Some numerical simulations are performed to illustrate the effectiveness of proposed method. Simulation results show high robustness of proposed method against noise (spurious and missing pulses) and unwanted jitter.

Traffic classification has recently gained much attention in both academic and industrial research communities. Many machine learning methods have been proposed to tackle this problem and have shown good results. However, when applied to traffic with out-of-sequence packets, the accuracy of existing machine learning approaches decreases dramatically. We observe the main reason is that the out-of-sequence packets change the spatial representation of feature vectors, which means the property of linear mapping relation among features used in machine learning approaches cannot hold any more. To address this problem, this paper proposes an Improved Dynamic Time Warping (IDTW) method, which can align two feature vectors using non-linear alignment. Experimental results on two real traces show that IDTW achieves better classification accuracy in out-of-sequence traffic classification, in comparison to existing machine learning approaches.

In this paper, we propose a robust registration method, named Bounded-Variables Least Median of Squares (BVLMS). It overcomes both the misassociations and the ill-conditioning due to the interactions between Bounded-Variables Least Squares (BVLS) and Least Median of Squares (LMS). Simulation results demonstrate the feasibility of this new registration method.

Binary sequences with low autocorrelation have important applications in communication systems and cryptography. In this paper, the autocorrelation values of binary Whiteman generalized cyclotomic sequences of order six and period pq are discussed. Our result shows that the autocorrelation of these sequences is four-valued and that the corresponding values are in {-1,3,-5,pq} if the parameters are chosen carefully.

For quantized control, one of the powerful approaches is to use a dynamic quantizer, which has internal memories for signal quantization, with a conventional controller in the feedback control loop. The design of dynamic quantizers has become a major topic, and a number of results have been derived so far. In this paper, we extend the authors' recent result on dynamic quantizers, and applied them to a more general class of nonlinear systems, called the nonaffine nonlinear systems. Based on the performance index representing the degradation caused by the signal quantization, we propose practical dynamic quantizers, which include the authors' former result as a special case. Moreover, we provide theoretical results on the performance and on the stability of the resulting quantized systems.

A joint superimposed sequence design, known as SuperImposed sequence for PAPR Reduction, or SIPR, using per-tone affine precoding technique is proposed to jointly estimate MIMO-OFDM channels and reduce the peak-to-average power ratio (PAPR) for MIMO-OFDM systems. The proposed technique optimizes the trade-off between BER, MSE of the channel estimate, and PAPR reduction performance. Moreover, it does not require side information to be transmitted for the removal of the sequence at the receiver, and the transmit redundancy can be as small as 1 symbol/subcarrier. The superimposed sequence is designed by solving a convex quadratically constrained quadratic programming problem and has a computational complexity comparable to previous technique using linear programming. It is shown that SIPR can be regarded as a generalization of the popular tone reservation (TR) technique, and thus, is able to outperform TR in terms PAPR reduction performance, with less transmit overhead. Simulation results and transmit redundancy analysis of SIPR and TR are shown to illustrate the efficacy of the proposed scheme.

The extensive study and design of Body Area Networks (BANs) and development of related applications have been an object of interest during the last few years. Indeed, the majority of applications have been developed to operate at frequencies up to X band. However nowadays, a new growing attention is being focused on moving the study of BANs to higher frequencies such as those in V andW bands. The characterization of the on-body propagation channel is therefore essential for the design of reliable mm-wave BAN systems. However the classical methods (FDTD, MoM, FEM) commonly used at lower frequencies are not computationally efficient at mm-wave due to the large amount of mesh elements needed to discretize an electrically large geometry such as the human body. To overcome this issue, a ray tracing technique, generally used for characterizing indoor propagation, has been used to analyze a specific channel: chest-to-belt link. The reliability of this high frequency method has been investigated in this paper considering three different test cases. Moreover, a comparison of simulations and measurements, both performed on a body centric scenario at 94GHz, is also presented as well.

We propose a maximum likelihood estimation approach for the recovery of continuously-defined sparse signals from noisy measurements, in particular periodic sequences of Diracs, derivatives of Diracs and piecewise polynomials. The conventional approach for this problem is based on least-squares (a.k.a. annihilating filter method) and Cadzow denoising. It requires more measurements than the number of unknown parameters and mistakenly splits the derivatives of Diracs into several Diracs at different positions. Moreover, Cadzow denoising does not guarantee any optimality. The proposed approach based on maximum likelihood estimation solves all of these problems. Since the corresponding log-likelihood function is non-convex, we exploit the stochastic method called particle swarm optimization (PSO) to find the global solution. Simulation results confirm the effectiveness of the proposed approach, for a reasonable computational cost.

In this paper, Hermite polynomial representation is proposed as an alternative way to represent finite fields of characteristic two. We show that multiplication in Hermite polynomial representation can be achieved with subquadratic space complexity. This representation enables us to find binomial or trinomial irreducible polynomials which allows us faster modular reduction over binary fields when there is no desirable such low weight irreducible polynomial in other representations. We then show that the product of two elements in Hermite polynomial representation can be performed as Toeplitz matrix-vector product. This representation is very interesting for NIST recommended binary field GF(2571) since there is no ONB for the corresponding extension. This representation can be used to obtain more efficient finite field arithmetic.

This letter deals with blind carrier frequency offset estimation by exploiting the minimum variance distortionless response (MVDR) criterion for interleaved uplink orthogonal frequency division multiple access (OFDMA). It has been shown that the complexity and estimation accuracy of MVDR strictly depend on the grid size used during the search. For the purpose of efficient estimation, we present an improved polynomial rooting estimator that is robust in low signal-to-noise ratio scenario. Simulation results are provided for illustrating the effectiveness of the proposed estimator.

A two-dimensional negative refractive index material is proposed. The material has a bulky structure composed of dielectric prism cells with metal patterns. The material is expressed by an equivalent circuit. The propagation regions of two left-handed modes calculated from the equivalent circuit exist near the propagation regions obtained by electromagnetic simulation. It is confirmed by simulation that the incident plane wave goes into the material with low reflection by using the second left-handed mode and attaching metal conversion strips around the material. A negative refractive index slab lens with 15×9 cells is made to measure the field distribution of wave out of the lens. It is shown that the resolution of the slab lens exceeds the diffraction-limit.

This paper contributes to k-error linear complexity of some generalized cyclotomic binary sequences of length 2pm and pm constructed in recent years. By defining related reference sequences, we find that these sequences possess very low k-error linear complexity for some certain values of the parameter k even though they have high linear complexity. Moreover, we point out that (p-1)-tuple distributions of all these sequences are not span. Thus they should be selected carefully for use in stream cipher systems.

In this letter, we consider the global exponential stabilization problem by output feedback for a class of nonlinear systems. Along with a newly proposed matrix inequality condition, the proposed control method has improved flexibility in dealing with nonlinearity, over the existing methods. Analysis and examples are given to illustrate the improved features of our control method.

Quantum steganography is to send secret quantum information through a quantum channel, such that an unauthorized user will not be aware of the existence of secret data. The depolarizing channel can hide quantum information by disguising it as channel errors of a quantum error-correcting code. We improve the efficiency of quantum steganography with noisy depolarizing channels, by modifying the twirling procedure and adding quantum teleportation. The proposed scheme not only meets the requirements of quantum steganography but also has higher efficiency.

Mutual information (MI) is a standard measure of statistical dependence of random variables. However, due to the log function and the ratio of probability densities included in MI, it is sensitive to outliers. On the other hand, the L2-distance variant of MI called quadratic MI (QMI) tends to be robust against outliers because QMI is just the integral of the squared difference between the joint density and the product of marginals. In this paper, we propose a kernel least-squares QMI estimator called least-squares QMI (LSQMI) that directly estimates the density difference without estimating each density. A notable advantage of LSQMI is that its solution can be analytically and efficiently computed just by solving a system of linear equations. We then apply LSQMI to dependence-maximization clustering, and demonstrate its usefulness experimentally.

In the Knill-Laflamme-Milburn (KLM) scheme, quantum teleportation is nearly deterministically carried out with linear optics. To reconstruct an original quantum state, however, a phase shift is required for an output state. We exhibit a proper phase shift to complete quantum teleportation.

The linearity analysis of a passive mixer is presented. The distortion mechanism caused by switching operation of a MOS transistor is elucidated from the static and dynamic analysis of passive mixers. Furthermore, the maximum input and output level to keep linear operation and its required bias conditions are expressed by simple equations. The maximum linear output amplitude of the passive mixer is determined only by the local signal amplitude and it does not depend on input and output impedance. The calculated linearity performances agree well with simulated and measured results.

We address the problem of processing graph pattern matching queries over a massive set of data graphs in this letter. As the number of data graphs is growing rapidly, it is often hard to process such queries with serial algorithms in a timely manner. We propose a distributed graph querying algorithm, which employs feature-based comparison and a filter-and-verify scheme working on the MapReduce framework. Moreover, we devise an efficient scheme that adaptively tunes a proper feature size at runtime by sampling data graphs. With various experiments, we show that the proposed method outperforms conventional algorithms in terms of scalability and efficiency.