Abstract: One of the most important tasks in opinion mining is opinion element extraction such as opinion expression, opinion holder and opinion target from a review text. Majority existing methods for opinion mining only concentrate on the review text itself. The mentality and influence of opinion holders is usually overlooked in opinion mining. The isolation of between opinion element extraction methods and mentality and influence of the opinion holder will make it very difficult for users to decide which mined opinions are worth being utilized. This paper introduces a novel concept of opinion network and proposes a PageRank-like algorithm called OHRank. It is first attempt to analyze the valuable opinion from the constructed opinion network by integrating mentality and influence of opinion holder into opinion mining. This proposed approach has been applied to real-world datasets and initial experiments indicate that the mentality and influence of opinion holder and his/her extra activity are helpful for finding valuable opinion and that the OHRank method outperforms benchmark methods that ignore those information.
Abstract: A low-voltage wide-tolerance-range passive UHF RFID tag's baseband logic design is presented in this paper. Based on deep submicron CMOS technologies, the design utilizes tailored techniques to satisfy subthreshold operation: to deal with the specific timing and wide-rangevariation problems at very low power supply, and for the consideration of limited availability of RF power. Compensated addition is proposed for the PIE decoder, and poweraware scheme is applied to the entire logic part. Galoi Linear feedback shift register (LFSR) and one-hot counter are also applied t ofulfill critical timing requirements. Additionally, these techniques help to improve clock efficiency and reduce the frequency variation impact in low-voltage data link portions. Therefore the robustness in subthreshold operation is ensured. The logic design was fabricated in 180nm, 130nm and 90nm CMOS technologies respectively to verify the compatibility. In measurement the designs indicate competent subthreshold operation. The 90nm version can function at 0.33V.
Abstract: Existing proxy signature schemes are not proved to have complete security in the provable security model for proxy signature, whether the schemes are secure needs to be further studied. We show a generalized provable security model for proxy signature. Comparing with Boldyreva's security model, we introduce Schuldt's work to our security model. We propose a secure proxy signature scheme, which is based on Waters' signature scheme in the standard model. Comparing with other proxy signature schemes having a reduction to CDH assumption in the standard model, our scheme is more secure and efficient.
Abstract: Most of implementations of the cryptanalytic time-memory trade-off attacks such as Hellman's original method, Rivest's distinguished points cracking and Oechslin's rainbow attack are also considered as an exhaustive attack to passwords in a limited length range on a certain charset. However, the distributions of structures and strings making up real human memorable passwords do not appear random. Based upon these, we propose a method to generate passwords in those cryptanalytic timememory trade-off methods. It achieves a higher hit ratio in attacking actual passwords and reduces search space drastically with requirement of only a little extra memory. It makes time-memory trade-off more practical. Even to attack long length passwords, the results of experiments show that our approach has a higher hit ratio compared with Oechslin's method. In addition, this method can be used in the distributed and parallel attack.
Abstract: Minimum attribute reduction in rough set theory is an NP-hard problem, which is difficult to use traditional evolution methods to solve. In this paper, a novel and efficient minimum Attribute reduction algorithm (named HERCo2AR) based on Hierarchical elitist role model combining competitive and cooperative coevolution is proposed. Through such an iterative process of competitive and cooperative coevolution, the various subpopulations are better optimized by different elitists, and reasonable decomposition of interacting attribute sets can coadapt to emerge due to the evolutionary pressure of hierarchical elitist role. The hierarchical elitist role model is very effective in the protection and promotion of outstanding individuals, and it can accelerate to direct the global optimal attribute reduction. Experimental results demonstrate that HERCo2AR achieves the better feasibility and effectiveness than existing state-of-the-art attribute reduction algorithms, and the quality of the global optimal solution can be signi-cantly improved as well.
Abstract: In this paper, a novel method for analyzing the noise characteristic of solar cells with En-In model was studied. The En-In noise model in two-port network was introduced to study the low-frequency noise characteristic of solar cells. According to the relationship between the output noise power spectrum and the two noise parameters in En-In noise model of the solar cell, known as En and In, an accurate method for extracting the two noise parameters was proposed. At the same time, the measurement method for the both parameters from 1Hz to 10kHz was studied. After 1/f noise curve fitting and characteristic frequency of G-R noise extraction on the noise spectrums of a large amount of solar cells, the analyzing results of spectrum compositions proved the validity and significance of the En-In noise model for noise analysis of solar cells. It also provided the essential theoretical and experimental basis for the further research on noise characteristic and reliability estimation of solar cells and PV modules.
Abstract: Arithmetical operations are fundamental in computing models. But arithmetic operations in membrane computing are restricted in integer field. In this paper, we present fraction arithmetic P systems for performing addition, subtraction, multiplication, division on fractions through designing the rules with priority. Some examples are given to illustrate how to compute the arithmetical fractions in these systems and show that the designed rules can carry out correct arithmetic computations of fractions.
Abstract: For the problem of security properties scale badly of the Direct anonymous attestation (DAA) scheme based symmetric bilinear pairing, a new DAA scheme based on asymmetric bilinear pairing, which gives a new practical solution to ECC-based TPM in protecting the privacy of TPM, is presented. The scheme takes on new process and framework in sign protocol, of which the TPM has only to perform three exponentiations, moreover, the signature which isn't knowledge of signature, is a signature of the ordinary ecliptic curve system itself. Compared to other schemes, the whole performance of the scheme is the best, and the scheme not only satisfies the same properties, but also is more simple and efficient. This paper gives not only a detailed security proof of the proposed scheme which shows that the scheme meets the security requirements of anonymity and unlinkability, but also a careful performance analysis by comparing with the existing DAA schemes.
Abstract: In this paper we generalize the iterative regularization method and the inverse scale space method, recently developed for wavelet-based image restoration, to curvelet-type decomposition spaces setting. We obtain the result that minimzer of the new model can be derived as curvelet firm shrinkage with curvelet-type weight, which is dynamically changing in the iteration(CDS-IRM). And we obtain a new class of nonlinear inverse scale spaces flow which is dependent on Curvelet-type decomposition scale and smooth order(CDS-ISS). Numerical experiments indicate that the proposed methods are very efficient for denoising.
Abstract: Amdahl's law is a simple and fundamental tool for understanding the evolution of performance as a function of parallelism. Following a recent trend on timing and power analysis of general purpose many-core chip using this law, we develop a novel PIP Panalytical model for evaluating the performance and power of hierarchical on-chip large-scale parallel architectures with the core number, super-node size, processing element number, and function unit number taken into consideration. We thereby investigate the influence of workload characteristics (Thread-level parallel TLP, Instruction-level parallel IL Pand Data-level parallel DLP) on resource allocation with the restriction of performance and power. The results provide some feasible options to design TOPS level DS Parchitecture as well as a theoretical basis for making the design more scalable.
Abstract: Due to the upcoming IPv4 address exhaustion, the transition from IPv4 to IPv6 becomes an urgent problem restricting the growth of Internet. Multi-NAT, which is desired in large scale IPv4-IPv6 coexistent network, has inherent difficulties in the stateful traffic balancing and failure recovery. The existing schemes cannot handle them due to the absence of state synchronization. In this paper we propose a novel Load balancer (LB) to build a Scalable multi-NAT (SMNAT) in large scale network for various IPv4-IPv6 coexistent scenarios. The LB is specifically designed to have a translation pattern related hash keys and load-balance bi-directional traffic in two modes. Additionally an Adaptive reassigning algorithm (ARA) running in LB is presented to schedule flows adaptively to reduce the cost of state synchronization as well as guarantee the performance in load balancing. Comparing SMNAT with the existing load balancing schemes, the simulation result shows that our SMNAT outperforms other schemes and meets the goals of large scale NAT.
Abstract: A recent methodology to model biochemical systems is here presented. It is based on a conceptual framework rooted in membrane computing and developed with concepts typical of discrete dynamical systems. According to our approach, from data observed at suitable macroscopic temporal scales, one can deduce, by means of algebraic and algorithmic procedures, a discrete model (calledMetabolic Psystem) which accounts for the experimental data, and opens the possibility to understand the systemic logic of the investigated phenomenon. The procedures of such a method have been implemented within a computational platform, a Java software called MetaPlab, processing data and simulating behaviors of metabolic models. In the paper, we briefly describe the theory underlying the modeling of biochemical systems by Metabolic Psystems, along with its development stages and the related extensive literature.
Abstract: In order to construct a high-quality graph to improve the learning accuracy, a new semi-supervised regression algorithm is proposed. According to all labeled and unlabeled samples, multiple graphs with different structures are constructed by using different edgeselection strategies and edge-measurement methods. Each graph corresponds to a basic graph kernel. Following that, a combined graph kernel is created by carrying out a convex optimization operation on these basic graph kernels. We can further obtain an optimal combined graph by calculating a pseudo-inverse of the combined graph kernel. Based on the optimal combined graph, a harmonic function is applied to solving the semi-supervised regression problem. Experimental results on typical artificial function and UCI real datasets show that, compared with other graphbased semi-supervised regression algorithms, the proposed algorithm has higher prediction accuracy even though its control parameters are not settled as optimum values.
Abstract: In this paper, a visual servo stabilization approach consisting in a dynamic switching control law for a nonholonomic mobile robot is presented, which applies the epipolar geometry and the 1D trifocal tensor to drive the robot to a desired configuration. The whole motion process is divided into three steps. Firstly, an epipolebased control law is designed to make the robot rotate in place until the camera points to the desired position. The 1D trifocal tensor is then used in the second translation step to reach the desired place. Finally, the desired configuration is reached through a pure rotation using the epipolar geometry. The stability of the proposed control system is proved based on linear system control theory and Lyapunov theory. Simulation results are given to illustrate the effectiveness of the proposed controller.
Abstract: Exemplar-based clustering algorithm is very efficient to handle large scale and high dimensional data, while it does not require the user to specify many parameters. For current algorithms, however, are the inabilities to identify the optimal results or specify the number of clusters automatically. To remedy these, in this work, we propose and explore the idea of exemplar-based clustering analysis optimized by genetic algorithms, abbreviated as ECGA framework, which use genetic algorithms for optimizing and combining the results. First, an exemplarbased clustering framework based on canonical genetic algorithm is introduced. Then the framework is optimized with three new genetic operators: (1) Geometry operator which limits the typology distribution of exemplars based on pair-wise distances, (2) EM operator which apply EM (Expectation maximization) algorithmto generate children from previous population and (3) Vertex substitution operator which is initialized with genetic algorithm and select exemplars by using the variable neighborhood search meta-heuristic framework. Theoretical analysis proves the ECGA can achieve better chance t ofind the optimal clustering results. Experimental results on several synthetic and real data sets show our ECGA provide comparable or better results at the cost of slightly longer CPU time.
Abstract: In some communication systems the transmitted signal is contaminated by impulsive noise with a non-Gaussian distribution. Non-Gaussian noise caused significant performance degradation to communication receivers. The new constant modulus blind equalizer based on Fractional lower-order statistics of the equalizer input, which is defined as FLOS_CMA, is able to mitigate impulsive channel noise while restoring the constant modulus character of the transmitted communication signal. However, like the Constant modulus algorithm (CMA), the steady-state Mean square error (MSE) of the FLOS_CMA algorithm may not be sufficient low for the system to obtain adequate performance. This paper proposes a concurrent equalizer, in which a Decision-directed least mean p norm (DD_LMP) equalizer operates cooperatively with a FLOS_CMA equalizer, controlled through a non-linear link. Simulation results using M-QAM and 8-PSK signaling have shown that besides the capability of compensating the phase offset, the proposed concurrent FLOS_CMA and DD_LMP blind equalizer has faster convergence rate and lower steady-state MSE than the FLOS_CMA approach.
Abstract: The Shannon-Nyquist sampling theorem for deterministic signals is a fundamental result in the field of telecommunication and signal processing, and many results on this topic have been obtained. However, very few results on random signals have been published, after Kolmogorov mentioned the importance of Shannon-formula for stochastic signals in 1956. In this paper, following the almost sure result for bandlimited stochastic processes proposed by Seip in 1990, we give an almost sure result of the classical sampling theorem for bandlimited random signals with local average sampling.
Abstract: The discovery of three-dimensional (3D) hand models corresponding to the user's 3D hand pose in initial frames is significant in 3D human hand tracking and interacting. This study proposes an approach to initialize 3D hand gestures for the user to have an easier, more pleasurable, and satisfactory experience. This paper covers the following points. First, a new approach to selecting a human hand gesture from the hand postures database is presented. Second, both techniques of visualization and human-computer interaction are used in the initialization process, through which the 3D human hand model is finetuned time after time until the required accuracy is satisfied. Lastly, the proposed initialization method is applied to our online virtual assembling system. We introduce a key factor to improve time cost of initialization. Our experimental results show that the proposed approach is not only fast, accurate, and robust but also direct, natural, and convenient for operators to handle.
Abstract: Moving cast shadow detection and removal is a key step for accurate object detection in intelligent transportation system. This paper proposes a robust cast shadow detection algorithm by integrating multiple cues. Firstly, a weak shadow detector is adopted to detect these potential shadow pixels; Then three adaptive shadow estimators are designed and cascaded to integrate texture, chromaticity, brightness as well as spatial-temporal context for eliminating the object pixels so that this algorithm can robustly detect the moving cast shadow in the various environments; Lastly, spatial adjustment is employed to verify the shadow detection results of these three shadow estimators. Experimental results on indoor and outdoor video sequences show that this proposed algorithm can robustly detect moving cast shadow and rapidly adapt to variations in traffic surveillance scenarios.
Abstract: In many applications, the Gaussian mixture serves as an important probabilistic representation of the system state. A global optimal Gaussian mixture reduction (GMR) approach based on Integer linear programming (ILP) is developed in this paper. Firstly, a Gaussian base set is constructed with partial merging of components of the original mixture. Secondly, by introducing auxiliary variables reasonably, the original problem of selecting the best candidates from the given Gaussian base set is formulated as an ILP problem. Finally, a global optimal solution to GMR is obtained by solving the ILP problem. The global optimum property enables it as a basis for performance comparison with different GMR algorithms.
Abstract: Minutiae-based algorithm plays a more and more important role in fingerprint recognition. It is greatly limited by its demand for good image quality and dependence on fingerprint aligning, especially for incomplete fingerprint recognition. Improved Genetic algorithm-Particle swarm optimization (GA-PSO) algorithm is applied to deal with these problems. The proposed algorithm improves GA-PSO in two aspects, population initialization based on reference point pre-aligning and fitness function construction based on fusion of minutiae-matching and orientationmatching. The experimental results on the FVC2004 show the high effectiveness and practicability of our algorithm.
Abstract: It is quite a great challenge for Contextaware recommender systems (CARS) to generate accurate recommendations with only a few available none-zero contextual user preferences. This paper presents a new approach to alleviate this high sparsity problem by applying the Higher order singular value decomposition (HOSVD) technique. Firstly, it constructs an N-order tensor to represent multidimensional contextual user preferences and decompose it into (N-2) 3-order tensors according to different types of context (such as time, location and activity). Secondly, it introduces HOSVD to automatically discover the latent associations among these different 3dimensional objects and predicts unknown unidimensional contextual user preferences. Finally, it calculates every contextual influence coefficient that each type of context factor influences user preferences and then constructs a new N-order tensor using weighted linearization method in order to provide recommendations. Experimental evaluation on a simulated personalized mobile services environment demonstrates the efficacy of our approach against the other baseline ones.
Abstract: To estimate the Direction-of-arrival (DOA) of a far-field wideband source using a linear array, the Time-difference-of-arrival (TDOA) based and Steeredresponse power (SRP) algorithms are of the most useful. In this paper, for white Gaussian signal and noise, the estimation variances of both the methods and the Cramer-Rao lower bound (CRLB) are derived in closed-form for a linear array. Meanwhile, a Gauss-Markov (GM) procedure is introduced to achieve optimal conversion of the estimated delay vectors for the TDOA based estimator. Moreover, a generalized SR Pestimator is proposed for the generalized case with nonuniform SNR.
Abstract: Many protocols have been proposed to increase efficiency and security of traditional protocols in Mobile ad-hoc networks (MANET), but they are all facing the problem of computation overhead which leads to impracticability. Adaptive routing strategy (ARS) is a novel routing strategy that switches routing protocol according to the network condition. Though this method alleviates the problem of efficiency, it doesn't cover the secure issues. We integrate our security mechanism based on Artificial immune system (AIS), with adaptive routing strategy to enhance efficiency and security. First we presented a more appropriate definition to the measurement of network condition, then we designed a secure adaptive routing strategy based on the definition. At last, we gave a performance analysis to validate the correctness and reliability of our scheme.
Abstract: Network virtualization provides a powerful tool to allow multiple networks, each customized to a specific purpose, to run on a shared substrate. However, a big challenge is how to map multiple virtual networks onto specific nodes and links in the shared substrate network, known as virtual network embedding problem. Previous works in virtual network embedding can be decomposed to two classes: two-stage virtual network embedding and onestage virtual network embedding. In this paper, by pruning the topology of virtual network using k-core decomposition, a hybrid virtual network embedding algorithm, with consideration of location constraints, is proposed to leverage the respective advantage of the two kinds of algorithm simultaneously in the mapping process. In addition, a time-oriented scheduling policy is introduced to improve the mapping performance. We conduct extensive simulations and the results show that the proposed algorithm has better performance in the long-term run.
Abstract: The Visual multi-secret sharing (VMSS) scheme is characterized by encoding several secret images into a set of noise-like shares. Most existing VMSS methods have to distort shares to embed additional secret images. As a result, the quality of the decoded original secret image is degraded. This paper proposes a folding-up operation based VMSS scheme, which is able to encode one secret image and a group of tag images into shares. The secret image is revealed by stacking all shares, and folding up each chosen share discloses the tag image. The proposed scheme encodes tag images without affecting the quality of the reconstructed secret image. The quality of the decoded secret image is equal to that of the conventional Visual secret sharing (VSS) scheme. The superiority of the proposed method is experimental verified.
Abstract: We investigate the structures and properties of one-Homogeneous (Lee) weight linear codes over the ring of integers modulo M (M is a power of a prime integer p) with one unique nonzero weight. We fully describe one-Homogeneous (Lee) weight codes over rings of integers modulo 4, 8 and 9. By the generalized Gray map, we obtain a class of optimal binary linear codes which reaches the Griesmer bound as well as the plotkin bound and a class of optimal p-ary (p is odd and prime) nonlinear codes which attains the Plotkin bound.
Abstract: High Peak-to-average power ratio (PAPR) has been a crucial problem in Orthogonal frequency division multiplexing (OFDM) systems. In all PAPR reduction schemes, Tone reservation (TR) technology is considered as one of the most promising methods because of no additional distortion, no side information, and low implementation cost. For conventional TR approaches, the assigned value to reserved subcarriers just considers one peak value and this brings peak value up again easily. In this paper, a novel scheme named Metric-based angle-rotated (MBAR) for TR is presented. The scheme employs a metric to measure how much each subcarrier contributes to the output signal samples of large magnitude and then subcarriers with the largest positive metrics are selected to reduce PAPR. The simulation results show that when the reserved subcarriers number is 1.46 percent, the PAPR gain of the proposed method can achieve 0.47dB at least at the probability of 10-3.
Abstract: In this paper, we propose a nonquadratic criterion to solve the Generalized eigenvalue decomposition (GED) problem. This criterion exhibits a single global maximum that is attained if and only if the weight matrix spans the principal generalized subspace. The other stationary points of this criterion are (unstable) saddle points. Since the criterion is nonquadratic, it has a steep landscape and, therefore, yields fast gradient-based algorithms. Applying the projection approximationmethod and Recursive least squares (RLS) technique, we develop an adaptive algorithm with low computational complexity to track the principal generalized subspace, as well as an adaptive algorithm to parallely estimate the principal generalized eigenvectors. Numerical results are provided to corroborate the proposed studie.
Abstract: This paper proposes an efficient interference mitigation and joint decoding scheme for uplink LDPC-coded relay cooperation over a Rayleigh fading channel, where a concatenation ofMinimum-mean-squared error linear detectors (MMSE) and BP-based joint iterative decoding based on the introduced treble-layer Tanner graph are effectively designed t ofilter and decode the corrupted received sequence at a base station. It is demonstrated by theoretical analysis and numerical simulations that the proposed design can well combine the gains from coding and diversity, which consequently leads to a significant performance improvement over the conventional cooperation system under the same conditions.
Abstract: The design of threshold based distributed Certification authority (CA) has been proposed to provide secure and efficient key management service in Mobile ad hoc networks (MANETs), but most of previous work ignore the efficiency and effectiveness and assuming there are always honest nodes performing the service. Focusing on developing a model to select a coalition of nodes dynamically and optimally to carry out the threshold key management service in MANETs, we formulate the dynamic nodes selection problem as combinatorial optimization problem, with the objectives of maximizing the success ratio of the service and minimizing the nodes' cost of security and energy, and then extend the payment structure of the classical Vickrey, Clarke and Groves (VCG) mechanism design framework to ensure truth-telling is the dominant strategy for any node in our scenario. Compared with existing works in the presence of selfish nodes, the proposed model enjoys an improvement of both the success ratio of key management service and lifetime of the network, and a reduction of both the cost of participating nodes and compromising probability of MANETs.
Abstract: Currently, few general methods have been suggested to quantitate the imperceptibility among various hiding algorithms. Especially, it is a challenge to quantitate the imperceptibility of the hiding-vector, which is consisted of orthogonal hiding algorithms in the multidimensional hiding space. In this paper, a novel model of general imperceptibility quantitation was proposed. According to this model, a quantitation method based on the relative entropy was designed. It is proved under this quantitation method that there exists the global maximal imperceptibility for any specified hiding-vector capacity. An optimization algorithm was proposed to approach this maximum by adjusting the allocation of secret message into each components of the hiding-vector. Experiments with VoI Pand bitmap multi-dimensional hiding space validated the effectiveness of the designed quantitation method and the proposed optimization algorithm.
Abstract: Differential power analysis (DPA) poses a great threat to cipher security circuit since it exploits the dependency between the processed data and the power consumption. Two-phase Sense amplifier based logic (Twophase SABL) suitable to DPA resistant logic style has been introduced under unbalanced load conditions. The proposed logic obtains constant energy consumption per clock cycle with pre-charge and evaluation phases. In this paper, Two-phase SABL cell and flip-flop are designed and simulated to confirm the energy balancing characteristic. Using TSM C0.13μm CMOS technique, simulation results show that the power consumption fluctuations in the flip-flop is decreased by 15.1% under unbalanced condition and the area is reduced by 38.4%.
Abstract: Coherent integration and non-coherent accumulation have been developed to acquire weak Global position system (GPS) signals. The threshold of acquisition algorithm is fixed, and is determined by the weakest signal. Strong signals and weak signals always coexist in the physical environment. A new method is presented for weak GPS signal acquisition using variable threshold. Through adjusting the thresholds with different noncoherent accumulation times, this method is applicable to all kinds of signals. It has wonderful acquisition efficiency through theory analysis and real signal verification, especially when strong signals and weak signals coexist, it can greatly reduce acquisition time.
Abstract: This paper investigates the reliable controller design for networked control system with probabilistic actuator faults under event-triggered scheme. The key idea is that only the newly states violating specified triggering condition will be transmitted to the controller. Considering the effect of the network transmission delay, event-triggered scheme and probabilistic actuator faults with different failure rates, a new actuator fault model is proposed. Criteria for the exponential stability and criteria for co-designing both the feedback and the trigger parameters are derived by using Lyapunov functional. These criteria are obtained in the form of linear matrix inequalities. A simulation example is employed to show the effectiveness of the proposed method.
Abstract: Anomaly detection generally gains wide attention in hyperspectral imagery for its high spectral resolution. Real-time processing is badly needed due to its large data set. This paper presents real-time processing versions to implement the commonly used RX anomaly detector which make use of information only provided by previous pixels prior to currently being processed pixel. Through these algorithms, hyperspectral image data can be processed timely. Experimental results demonstrate these new real-time versions significantly solve real-time processing problem compared to conventional anomaly detector.
Abstract: The flight data generated during airplane's flights can be used for fault diagnosis, which is of great importance for improving the security and reducing the cost of maintenance of airplanes. It's an important fault diagnosis method t ofind out novel patterns of flight data, but flight data has characteristics of high dimension and containing stochastic noise. In this paper, we take advantage of similarity querying method t ofind out novel patterns in order to reduce the negative effect brought by high dimension and stochastic noise. Firstly, we reduce the dimension and eliminate the stochastic noise of flight data by piecewise linear representation method. Then, the indexical tree based on distance reduction rate is created to achieve efficient search. At last, the proposed approach is evaluated with a series of experiments on simulative data and real-world data. The experimental results show that this method can be successfully applied in practice.
Abstract: A novel Dual-band bandpass filter (DBBPF) with an asymmetric topology and steppedimpedance Conductor-backed asymmetric coplanar waveguide (CBACPW) resonators is proposed in this paper. Compared with the existing DBBPFs with a same low-pass prototype, two additional transmission zeros are emerged by using the asymmetric topology. To facilitate the filter synthesis, design formulas of the filter are derived, and an ANN-based synthesis model of CBACPWs is developed. To validate the filter synthesis method, a DBBPF operating at GSM and GPS bands is designed, simulated and measured. A good agreement between simulation and measurement is obtained.
Abstract: The effect on the propagation characteristics of the electromagnetic waves by the second-order radiation of the moving high-speed train is analyzed in this paper. Two Lorentz transformations, one from the stationary reference coordinate system to the moving system and the other vice versa, are employed to derive the theoretical model for analysis of the propagation characteristics of the vertical polarized plane time-harmonic waves, which is oblique incidence to the train. The calculation results show that for the transmitting wave reflected by the moving high-speed train, two main signals can be received. One is at the transmitting frequency and the other is at the second-order radiated frequency. The frequency spectrum between these tw ofrequencies are much larger than which is introduced by the Doppler shift. The frequency and the reflection angle of the reflected wave are no longer equal to the frequency and the incident angle of the incident wave. The changed reflection frequency and angle are related to the train's velocity, the incident angle and the azimuth angle of the incident wave. The frequency shift is mainly decided by the y-component of the train's velocity. It has nothing to do with x-component of the train's velocity. The reflection angles will be smaller than the related incident angles when the train goes along -y direction. The reflection angles will be larger than the related incident angles when the train goes along +y direction. The reflection angle will become larger and larger with the increase of the incident angle and the y-component of the train's velocity. The induced current density and the charge density on the surface of the train are increased with the train's velocity, and the induced charge is much smaller than the induced current.