Space is becoming increasingly congested and contested, which calls for effective means to conduct effective monitoring of high-value space assets, especially in Space Situational Awareness (SSA) missions, while there are imperfections in existing methods and corresponding algorithms. To overcome such a problem, this letter proposes an algorithm for accurate Connected Element Interferometry (CEI) in SSA based on more interpolation information and iterations. Simulation results show that: (i) after iterations, the estimated asymptotic variance of the proposed method can basically achieve uniform convergence, and the ratio of it to ACRB is 1.00235 in δ0 ∈ [-0.5, 0.5], which is closer to 1 than the current best AM algorithms; (ii) In the interval of SNR ∈ [-14dB, 0dB], the estimation error of the proposed algorithm decreases significantly, which is basically comparable to CRLB (maintains at 1.236 times). The research of this letter could play a significant role in effective monitoring and high-precision tracking and measurement with significant space targets during futuristic SSA missions.

Pairing computations on elliptic curves with odd prime degrees are rarely studied as low efficiency. Recently, Clarisse, Duquesne and Sanders proposed two new curves with odd prime embedding degrees: BW13-P310 and BW19-P286, which are suitable for some special cryptographic schemes. In this paper, we propose efficient methods to compute the optimal ate pairing on this types of curves, instantiated by the BW13-P310 curve. We first extend the technique of lazy reduction into the finite field arithmetic. Then, we present a new method to execute Miller's algorithm. Compared with the standard Miller iteration formulas, the new ones provide a more efficient software implementation of pairing computations. At last, we also give a fast formula to perform the final exponentiation. Our implementation results indicate that it can be computed efficiently, while it is slower than that over the (BLS12-P446) curve at the same security level.

This letter proposes a numerical method for approximating the location of and dynamics on a class of chaotic saddles. In contrast to the conventional strategy of maximizing the escape time, our proposal is to impose a zero-expansion condition along transversely repelling directions of chaotic saddles. This strategy exploits the existence of skeleton-forming unstable periodic orbits embedded in chaotic saddles, and thus can be conveniently implemented as a variant of subspace Newton-type methods. The algorithm is examined through an illustrative and another standard example.

In this letter, we analyze performances of a frequency offset estimation based on the maximum likelihood criterion and provide a theoretical proof that the mean squared error of the estimation grows with increase in the offset. Moreover, we propose a new iterative offset estimation method based on the analysis. By computer simulations, we show that the proposed estimator can achieve the lowest estimation error after a few iterations.

A bi-dimensional empirical mode decomposition (BEMD) is one of the powerful methods for decomposing non-linear and non-stationary signals without a prior function. It can be applied in many applications such as feature extraction, image compression, and image filtering. Although modified BEMDs are proposed in several approaches, computational cost and quality of their bi-dimensional intrinsic mode function (BIMF) still require an improvement. In this paper, an iteration-free computation method for bi-dimensional empirical mode decomposition, called iBEMD, is proposed. The locally partial correlation for principal component analysis (LPC-PCA) is a novel technique to extract BIMFs from an original signal without using extrema detection. This dramatically reduces the computation time. The LPC-PCA technique also enhances the quality of BIMFs by reducing artifacts. The experimental results, when compared with state-of-the-art methods, show that the proposed iBEMD method can achieve the faster computation of BIMF extraction and the higher quality of BIMF image. Furthermore, the iBEMD method can clearly remove an illumination component of nature scene images under illumination change, thereby improving the performance of text localization and recognition.

Nowadays, with the extensive use of smart devices, the amount of mobile data is experiencing an exponential growth. As a result, accommodating the large amount of traffic is important for the future 5G mobile communication. Millimeter-wave band, which has a lot of spectrum resources to meet the demand brought by the growth of mobile data, is becoming an important part of 5G technology. In order to mitigate the high path loss brought by the high frequency band, beamforming is often used to enhance the gain of a link. In this paper, we propose an iteration-based beamforming method for planar phased array. When compared to a linear array, a planar phased array points a smaller area which ensures a better link performance. We deduce that different paths of millimeter-wave channel are approximately orthogonal when the antenna array is large, which forms the basis of our iterative approach. We also discuss the development of the important millimeter-wave device-phase shifter, and its effect on the performance of the proposed beamforming method. From the simulation, we prove that our method has a performance close to the singular vector decomposition (SVD) method and is superior to the method in IEEE802.15.3c. Moreover, the channel capacity of the proposed method is at most 0.41bps/Hz less than the SVD method. We also show that the convergence of the proposed method could be achieved within 4 iterations and a 3-bit phase shifter is enough for practical implementation.

The three dimensional (3D) reconstruction of a medical image sequence can provide intuitive morphologies of a target and help doctors to make more reliable diagnosis and give a proper treatment plan. This paper aims to reconstruct the surface of a renal corpuscle from the microscope renal biopsy image sequence. First, the contours of renal corpuscle in all slices are extracted automatically by using a context-based segmentation method with a coarse registration. Then, a new coevolutionary-based strategy is proposed to realize a fine registration. Finally, a Gauss-Seidel iteration method is introduced to achieve a non-rigid registration. Benefiting from the registrations, a smooth surface of the target can be reconstructed easily. Experimental results prove that the proposed method can effectively register the contours and give an acceptable surface for medical doctors.

In this paper, a novel scheme of the adaptive sampling of block compressive sensing is proposed for natural images. In view of the contents of images, the edge proportion in a block can be used to represent its sparsity. Furthermore, according to the edge proportion, the adaptive sampling rate can be adaptively allocated for better compressive sensing recovery. Given that there are too many blocks in an image, it may lead to a overhead cost for recording the ratio of measurement of each block. Therefore, K-means method is applied to classify the blocks into clusters and for each cluster a kind of ratio of measurement can be allocated. In addition, we design an iterative termination condition to reduce time-consuming in the iteration of compressive sensing recovery. The experimental results show that compared with the corresponding methods, the proposed scheme can acquire a better reconstructed image at the same sampling rate.

In this paper, the multicell distributed beamforming (MDBF) design problem of suppressing intra-cell interference (InCI) and inter-cell interference (ICI) is studied. To start with, in order to decrease the InCI and ICI caused by a user, we propose a gradient-iteration altruistic algorithm to derive the beamforming vectors. The convergence of the proposed iterative algorithm is proved. Second, a metric function is established to restrict the ICI and maximize cell rate. This function depends on only local channel state information (CSI) and does not need additional CSIs. Moreover, an MDBF algorithm with the metric function is proposed. This proposed algorithm utilizes gradient iteration to maximize the metric function to improve sum rate of the cell. Finally, simulation results demonstrate that the proposed algorithm can achieve higher cell rates while offering more advantages to suppress InCI and ICI than the traditional ones.

In this article we present a novel corpus-based method for inducing romanization systems for languages through a bilingual alignment of transliteration word pairs. First, the word pairs are aligned using a non-parametric Bayesian approach, and then for each grapheme sequence to be romanized, a particular romanization is selected according to a user-specified criterion. As far as we are aware, this paper is the only one to describe a method for automatically deriving complete romanization systems. Unlike existing human-derived romanization systems, the proposed method is able to discover induced romanization systems tailored for specific purposes, for example, for use in data mining, or efficient user input methods. Our experiments study the romanization of four totally different languages: Russian, Japanese, Hindi and Myanmar. The first two languages already have standard romanization systems in regular use, Hindi has a large number of diverse systems, and Myanmar has no standard system for romanization. We compare our induced romanization system to existing systems for Russian and Japanese. We find that the systems so induced are almost identical to Russian, and 69% identical to Japanese. We applied our approach to the task of transliteration mining, and used Levenshtein distance as the romanization selection criterion. Our experiments show that our induced romanization system was able to match the performance of the human created system for Russian, and offer substantially improved mining performance for Japanese. We provide an analysis of the mechanism our approach uses to improve mining performance, and also analyse the differences in characteristics between the induced system for Japanese and the official Japanese Nihon-shiki system. In order to investigate the limits of our approach, we studied the romanization of Myanmar, a low-resource language with a large vocabulary of graphemes. We estimate the approximate corpus size required to effectively romanize the most frequency k graphemes in the language for all values of k up to 1800.

Existing pose estimation algorithms suffer from either low performance or heavy computation cost. In this letter, we present an approach to improve the attractive algorithm called Orthogonal Iteration. A new form of fundamental equations is derived which reduces the computation cost significantly. And paraperspective camera model is used instead of weak perspective camera model during initialization which improves the stability. Experiment results validate the accuracy and stability of the proposed algorithm and show that its computational complexity is favorably compare to the O(n) non-iterative algorithm.

A new class of almost quadriphase sequences with four zero elements of period 4N, where N ≡ 1(mod 4) being a prime, is constructed. The maximum nontrivial autocorrelations of the constructed almost quadriphase sequences are shown to be 4.

The contribution of this paper is two-fold. Firstly, we conduct a large-scale real-world evaluation of the effectiveness of integrating an automatic transliteration system with a machine translation system. A human evaluation is usually preferable to an automatic evaluation, and in the case of this evaluation especially so, since the common machine translation evaluation methods are affected by the length of the translations they are evaluating, often being biassed towards translations in terms of their length rather than the information they convey. We evaluate our transliteration system on data collected in field experiments conducted all over Japan. Our results conclusively show that using a transliteration system can improve machine translation quality when translating unknown words. Our second contribution is to propose a novel Bayesian model for unsupervised bilingual character sequence segmentation of corpora for transliteration. The system is based on a Dirichlet process model trained using Bayesian inference through blocked Gibbs sampling implemented using an efficient forward filtering/backward sampling dynamic programming algorithm. The Bayesian approach is able to overcome the overfitting problem inherent in maximum likelihood training. We demonstrate the effectiveness of our Bayesian segmentation by using it to build a translation model for a phrase-based statistical machine translation (SMT) system trained to perform transliteration by monotonic transduction from character sequence to character sequence. The Bayesian segmentation was used to construct a phrase-table and we compared the quality of this phrase-table to one generated in the usual manner by the state-of-the-art GIZA++ word alignment process used in combination with phrase extraction heuristics from the MOSES statistical machine translation system, by using both to perform transliteration generation within an identical framework. In our experiments on English-Japanese data from the NEWS2010 transliteration generation shared task, we used our technique to bilingually co-segment the training corpus. We then derived a phrase-table from the segmentation from the sample at the final iteration of the training procedure, and the resulting phrase-table was used to directly substitute for the phrase-table extracted by using GIZA++/MOSES. The phrase-table resulting from our Bayesian segmentation model was approximately 30% smaller than that produced by the SMT system's training procedure, and gave an increase in transliteration quality measured in terms of both word accuracy and F-score.

In this paper, two constructions of mutually orthogonal zero correlation zone polyphase sequence sets are presented. The first one is based on DFT matrices and interleaving iteration. After each recursive step, the period of sequence and the length of zero-correlation zone are two times larger than that in the last step. The second method, based on DFT matrices and orthogonal matrices, can generate numbers of mutually orthogonal optimal ZCZ sequence sets whose parameters reach the theoretical bounds by using interleaving and shifting techniques. As a result, the algorithms proposed can provide more sequences for the QS-CDMA (quasi-synchronous CDMA) systems.

This paper proposes a new hybrid method for machine transliteration. Our method is based on combining a newly proposed two-step conditional random field (CRF) method and the well-known joint source channel model (JSCM). The contributions of this paper are as follows: (1) A two-step CRF model for machine transliteration is proposed. The first CRF segments a character string of an input word into chunks and the second one converts each chunk into a character in the target language. (2) A joint optimization method of the two-step CRF model and a fast decoding algorithm are also proposed. Our experiments show that the joint optimization of the two-step CRF model works as well as or even better than the JSCM, and the fast decoding algorithm significantly decreases the decoding time. (3) A rapid development method based on a weighted finite state transducer (WFST) framework for the JSCM is proposed. (4) The combination of the proposed two-step CRF model and JSCM outperforms the state-of-the-art result in terms of top-1 accuracy.

Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers in observed rewards. In this paper, we propose an alternative method that employs the absolute loss for enhancing robustness and reliability. The proposed method is formulated as a linear programming problem which can be solved efficiently by standard optimization software, so the computational advantage is not sacrificed for gaining robustness and reliability. We demonstrate the usefulness of the proposed approach through a simulated robot-control task.

A novel construction of complementary sequences with multi-width zero cross-correlation zone (ZCCZ) is presented based on the interleaving iteration of a basic kernel set. The presented multi-width ZCCZ complementary (MWZC) sequences can be divided into multiple sequence groups, the correlation functions of which possess one-width intragroup ZCCZ and multi-width intergroup ZCCZ. When an arbitrary orthogonal sequence set with set size equal to sequence length is used as a basic kernel set, the constructed MWZC sequence set and the combination sets of specific subsets with each subset including several groups can be optimal with respect to the theoretical bound on set size. In addition, the MWZC sequence set includes complementary sequence sets with one-width or two-width ZCCZ as special subsets, and allows a more flexible choice of sequence parameters.

In this letter, we present a multiple-input multiple-output (MIMO) optimal combining (OC) scheme based on alternate iteration. With the channel state information (CSI) of co-channel interferers (CCIs), this algorithm can be used in flat fading and frequency selective channels to suppress CCIs. Compared with the optimal transceiver of MIMO maximal ratio combining (MRC) systems, results of simulation show that this scheme improves the uplink transmission performance significantly.

Graph matching is a NP-Hard problem. In this paper, we relax the admissible set of permutation matrices and meantime incorporate a barrier function into the objective function. The resulted model is equivalent to the original model. Alternate iteration algorithm is designed to solve it. It is proven that the algorithm proposed is locally convergent. Our experimental results reveal that the proposed algorithm outperforms the algorithm in .

Weighted graph matching is computationally challenging due to the combinatorial nature of the set of permutations. In this paper, a new relaxation approach to weighted graph matching is proposed, by which a new matching algorithm, named alternate iteration algorithm, is designed. It is proved that the algorithm proposed is locally convergent. Experiments are presented to show the effectiveness of the proposed algorithm.