An online nonnegative matrix factorization (NMF) algorithm based on recursive least squares (RLS) is described in a matrix form, and a simplified algorithm for a low-complexity calculation is developed for frame-by-frame online audio source separation system. First, the online NMF algorithm based on the RLS method is described as solving the NMF problem recursively. Next, a simplified algorithm is developed to approximate the RLS-based online NMF algorithm with low complexity. The proposed algorithm is evaluated in terms of audio source separation, and the results show that the performance of the proposed algorithms are superior to that of the conventional online NMF algorithm with significantly reduced complexity.

The measurement accuracy of frequency difference of arrival (FDOA) is usually determinant for emitters location system using rapidly moving receivers. The classic technique of expanding the integration time of the cross ambiguity function (CAF) to achieve better performance of FDOA is likely to incur a significant computational burden especially for wideband signals. In this paper, a nonconsecutive short-time CAF's methods is proposed with expansion of root mean square (RMS) integration time, instead of the integration time, and a factor of estimation precision improvement is given which is relative to the general consecutive method. Furthermore, by analyzing the characteristic of coherent CAF and the influence of FDOA rate, an upper bound of the precision improvement factor is derived. Simulation results are provided to confirm the effectiveness of the proposed method.

In this letter, a new and accurate frequency estimation method of complex exponential signals is proposed. The proposed method divides the signal samples into several identical segments and sums up the samples belonging to the same segment respectively. Then it utilizes fast Fourier transform (FFT) algorithm with zero-padding to obtain a coarse estimation, and exploits three Fourier coefficients to interpolate a fine estimation based on least square error (LSE) criterion. Numerical results show that the proposed method can closely approach the Cramer-Rao bound (CRB) at low signal-to-noise ratios (SNRs) with different estimation ranges. Furthermore, the computational complexity of the proposed method is proportional to the estimation range, showing its practical-oriented ability. The proposed method can be useful in several applications involving carrier frequency offset (CFO) estimation for burst-mode satellite communications.

In this paper, a miniaturized absorptive/transmissive radome with switchable passband and wide absorbing band is designed. Pin diodes are loaded on the radome in order to obtain switchable passband and miniaturized unit cells, while the resistor loaded double square loops are used to absorb the incident wave. The total thickness of the radome is only 4.5mm. Its transmission and absorbing properties are verified by both synthetic experiments and measurements in the anechoic chamber. Furthermore, the switchable passband of the radome is also evaluated using a waveguide simulator.

In this paper, for an odd prime p, two positive integers n, m with n=2m, and pm≡1 (mod 4), we derive an upper bound on the magnitude of the cross-correlation function between two decimated sequences of a p-ary m-sequence. The two decimation factors are 2 and 2(pm+1), and the upper bound is derived as $rac{3}{2}p^m + rac{1}{2}$. In fact, those two sequences correspond to the p-ary sequences used for the construction of Kasami sequences decimated by 2. This result is also used to obtain an upper bound on the cross-correlation magnitude between a p-ary m-sequence and its decimated sequence with the decimation factor $d=rac{(p^m +1)^2}{2}$.

High Efficiency Video Coding is a new video coding standard after H.264/AVC. By introducing a flexible coding unit, which can be recursively divided from 64×64 to 8×8 blocks in a Quadtree-Structure, HEVC achieves significantly higher coding efficiency than the previous standards. With the flexible CU structure, HEVC can effectively adapt to highly varying contents with a smaller CU or to flat contents with a larger CU, making it suitable for applications from mobile video to super high definition television. On the other hand, CU division does incur high computational cost for HEVC. In this paper, we propose a simple and fast CU division algorithm by using only a subset of pixels to determine when CU division happens. Experiment results show that our algorithm can achieve prediction quality close to HEVC Test Model with much lower computational cost.

In this paper, we consider optimal sensing scheduling for sequential cooperative spectrum sensing (SCSS) technique in cognitive radio networks (CRNs). Activities of primary users (PU) on a primary channel are captured by using a two states discrete time Markov chain process and a soft combination is considered at the FC. Based on the theory of optimal stopping, we propose an algorithm to optimize the cooperative sensing process in which the FC sequentially asks each CU to report its sensing result until the stopping condition that provides the maximum expected throughput for the CRN is satisfied. Simulation result shows that the performance of the proposed scheme can be improved by further shortening the reporting overhead and reducing the probability of false alarm in comparison to other schemes in literature. In addition, the collision ratio on the primary channel is also investigated.

Recently, several methods to process continuous queries for mobile objects in broadcast environments have been proposed. We propose a new indexing method for processing continuous queries that uses vector information in broadcast environments. We separate the index structure according to the velocities of the objects to avoid unnecessary accesses. The index structure consists of the index files for the slow moving objects and the fast moving objects. By avoiding unnecessary accesses, we reduce the tuning time to process a query in broadcast environments. To show the superiority of the proposed method, we evaluate its performance from various perspectives.

In general, tunnel diodes exhibit various types of oscillation mode: the sinusoidal mode or the nonsinusoidal mode which is known as the relaxation oscillation (RO) mode. We derive a condition for generating the RO in resonant tunneling diodes (RTDs) with essential components for equivalent circuit model. A conditional equation to obtain sufficient nonlinearity towards the robust RO is clarified. Moreover, its condition also can be applied in case of a bow-tie antenna integrated RTD, thus a design policy to utilize the RO region for the antenna integrated RTD is established by numerical evaluations of time-domain large-signal nonlinear analysis towards a terahertz transmitter for broadband wireless communications.

To improve the quality of waveforms and achieve a high input power factor (IPF) for matrix rectifier, a novel quasi sliding mode control (SMC) with adaptive compensation is proposed in this letter. Applying quasi-SMC can effective obviate the disturbances of time delay and spatial lag, and SMC based on continuous function is better than discontinuous function to eliminate the chattering. Furthermore, compared with conventional compensation, an adaptive quasi-SMC compensation without any accurate detection for internal parameters is easier to be implementated, which has shown a superior advance. Theoretical analysis and experiments are carried out to validate the correctness of the novel control scheme.

With the advances in computer processing that have yielded an enormous increase in performance, numerical analytical approaches based on electromagnetic theory have recently been applied to mobile radio propagation analysis. One such approach is the ray-tracing method based on geometrical optics and the uniform geometrical theory of diffraction. In this paper, ray-tracing techniques that have been proposed in order to improve computational accuracy and speed are surveyed. First, imaging and ray-launching methods are described and their extended methods are surveyed as novel fundamental ray-tracing techniques. Next, various ray-tracing acceleration techniques are surveyed and categorized into three approaches, i.e., deterministic, heuristic, and brute force. Then, hybrid methods are surveyed such as those employing Physical optics, the Effective Roughness model, and the Finite-Difference Time-Domain method that have been proposed in order to improve analysis accuracy.

The purpose of DNA sequencing is to determine the order of nucleotides within a DNA molecule of target. The target DNA molecules are fragmented into short reads, which are short fixed-length subsequences composed of ‘A’, ‘C’, ‘G’ ‘T’, by next generation sequencing (NGS) machine. To reconstruct the target DNA from the short reads using a reference genome, which is a representative example of a species that was constructed in advance, it is necessary to determine their locations in the target DNA from where they have been extracted by aligning them onto the reference genome. This process is called short read mapping, and it is important to improve the performance of the short read mapping to realize fast DNA sequencing. We propose three types of FPGA acceleration methods based on hash table; (1) sorting and parallel comparison, (2) matching that allows one mutation to reduce the number of the candidates, (3) optimized hash function using variable masks. The first one reduces the number of accesses to off-chip memory to avoid the bottleneck by access latency. The second one enables to reduce the number of the candidates without degrading mapping sensitivity by allowing one mutation in the comparison. The last one reduces hash collisions using a table that was calculated from the reference genome in advance. We implemented the three methods on Xilinx Virtex-7 and evaluated them to show their effectiveness of them. In our experiments, our system achieves 20 fold of processing speed compared with BWA, which is one of the most popular mapping tools. Furthermore, we shows that the our system outperforms one of the fastest FPGA short read mapping systems.

This paper provides a new method to correct annotation errors in a treebank. The previous error correction method constructs a pseudo parallel corpus where incorrect partial parse trees are paired with correct ones, and extracts error correction rules from the parallel corpus. By applying these rules to a treebank, the method corrects errors. However, this method does not achieve wide coverage of error correction. To achieve wide coverage, our method adopts a different approach. In our method, we consider that if an infrequent pattern can be transformed to a frequent one, then it is an annotation error pattern. Based on a tree mining technique, our method seeks such infrequent tree patterns, and constructs error correction rules each of which consists of an infrequent pattern and a corresponding frequent pattern. We conducted an experiment using the Penn Treebank. We obtained 1,987 rules which are not constructed by the previous method, and the rules achieved good precision.

A digital image is often deteriorated by impulse noise that may occur during processes such as transmission. An impulse noise converts the pixel data in the image into black (0) or white (255) values at a random frequency and is also called salt-and-pepper noise. In this paper, we identify the details of pixels that have been damaged by impulse noise by analyzing the frequency of the noisy image using non-harmonic analysis (NHA). From experimental results, we can confirm that this method shows superior performance compared to the recent PSNR denoising method. In addition, we show that the proposed method is particularly superior in eliminating impulse noise in images with high noise rates.

In this letter, we present a novel method for reconstructing continuous data field from scattered point data, which leads to a more characteristic visualization result by volume rendering. The gradient distribution of scattered point data is analyzed for local feature investigation via singular-value decomposition. A data-adaptive ellipsoidal shaped function is constructed as the penalty function to evaluate point weight coefficient in MLS approximation. The experimental results show that the proposed method can reduce the reconstruction error and get a visualization with better feature discrimination.

We regard a De Bruijn sequence of order n as a bijection on $mathbb{F}_2^n$ and consider the transition mappings between them. It is shown that there are only two conjugate transformations that always transfer De Bruijn sequences to De Bruijn sequences.

The translation based language model (TRLM) is state-of-the-art method to solve the lexical gap problem of the question retrieval in the community-based question answering (cQA). Some researchers tried to find methods for solving the lexical gap and improving the TRLM. In this paper, we propose a new dependency based model (DM) for the question retrieval. We explore how to utilize the results of a dependency parser for cQA. Dependency bigrams are extracted from the dependency parser and the language model is transformed using the dependency bigrams as bigram features. As a result, we obtain the significant improved performances when TRLM and DM approaches are effectively combined.

In this paper, we proposed a method for radar modulation identification based on the measurement of inequality in the frequency domain. Gini's coefficient was used to exploit the inequality in the powers of spectral components. The maximum likelihood classifier was used to classify the detected radar signal into four types of modulations: unmodulated signal (UM), linear frequency modulation (LFM), non-linear frequency modulation (NLFM), and frequency shift keying (FSK). The simulation results demonstrated that the proposed method achieves an overall identification accuracy of 98.61% at a signal-to-noise ratio (SNR) of -6dB without a priori information such as carrier frequency, pulse arrival times or pulse width.

The development of smart devices has led to the growth of Location-Based Social Networking Services (LBSNSs). In this paper, we introduce an l-Close Range Friends query that finds all l-hop friends of a user within a specified range. We also propose a query processing method on Social Grid Index (SGI). Using real datasets, the performance of our method is evaluated.

This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.