This paper addresses a noise matching problem for MIMO receiver with mutual coupling in the presence of signal and antenna noise coupling. The matching network in this paper is designed to maximize the system's ergodic capacity by means of minimizing the noise figure matrix. For reducing RF circuit complexity, low noise matching design without crossover elements of the matching circuit is derived for compact symmetrical 2$ imes$2 MIMO receiver system with mutually coupled antenna. Numerical simulation verifies our analytical results and demonstrates the superiority of the proposed matching method among feasible ones. The paper furthermore investigates the lossy matching circuit with the corresponding circuit parameters in a specific condition and the effect of practical matching circuit.

Anomaly detection has several practical applications in different areas, including intrusion detection, image processing, and behavior analysis among others. Several approaches have been developed for this task such as detection by classification, nearest neighbor approach, and clustering. This paper proposes alternative clustering algorithms for the task of anomaly detection. By employing a weighted kernel extension of the least squares fitting of linear manifolds, we develop fuzzy clustering algorithms for kernel manifolds. Experimental results show that the proposed algorithms achieve promising performances compared to hard clustering techniques.

With the development of the Internet, there are more and more shared resources on the Web. Personalized search becomes increasingly important as users demand higher retrieval quality. Personalized search needs to take users' personalized profiles and information needs into consideration. Collaborative tagging (also known as folksonomy) systems allow users to annotate resources with their own tags (features) and thus provide a powerful way for organizing, retrieving and sharing different types of social resources. To capture and understand user preferences, a user is typically modeled as a vector of tag: value pairs (i.e., a tag-based user profile) in collaborative tagging systems. In such a tag-based user profile, a user's preference degree on a group of tags (i.e., a combination of several tags) mainly depends on the preference degree on every individual tag in the group. However, the preference degree on a combination of tags (a tag-group) cannot simply be obtained from linearly combining the preference on each tag. The combination of a user's two favorite tags may not be favorite for the user. In this article, we examine the limitations of previous tag-based personalized search. To overcome their problems, we model a user profile based on combinations of tags (tag-groups) and then apply it to the personalized search. By comparing it with the state-of-the-art methods, experimental results on a real data set shows the effectiveness of our proposed user profile method.

This paper proposes a new small multiband printed antenna for wireless telecommunications modules that can realize Machine-to-Machine applications. We reconfigure our previous antenna to cover the 700MHz, 800MHz, and 900MHz bands, and add two new elements (second strips) to cover the 2GHz band. The new antenna achieves operation in quad-bands: 700MHz, 800MHz, 900MHz, and 2GHz. Frequency characteristics are analyzed using electromagnetic-simulation software based on the method of moments, and the validity of the numerical results is shown based on measured Voltage Standing Wave Ratio (VSWR) characteristics and the radiation patterns of a prototype antenna. The proposed antenna is compact with a VSWR bandwidth (≤2) of 27.5% in bands including 700MHz, 800MHz, and 900MHz, and a VSWR bandwidth (≤2) of 10.6% in the band including 2GHz. We clarify that the operating mechanism in the 2GHz band is equivalent to that of a one wavelength folded offset fed dipole antenna comprising a monopole element and second strips, and that the operating frequency in the 2GHz band can be determined by the path length from the tip of the monopole element to the tip of the second strip via a feeding point.

This paper proposes a compact three-mode H-shaped resonator bandpass filter fed by antiparallel coupled input/output lines. To investigate the resonant behavior of the H-shaped resonator, even/odd-mode resonance conditions of the resonator are first derived analytically. The multimode resonances of the H-shaped resonator filter are modeled by a multipath circuit formed with resonance paths. Moreover, a direct source/load coupling path is connected in parallel, of which the value shows a frequency dependency because of the antiparallel coupled feeding lines, thereby generating four transmission zeros (TZs) greater than the number of a theoretical limitation. The H-shaped resonator bandpass filter is synthesized, developed, and tested, showing a third-order passband response with four TZs located near the passband, and a wide stopband property.

This paper presents the design and radiation properties of a linearly polarized radial line microstrip antenna array (RL-MSAA) with U-slot circular microstrip antennas. A circular microstrip antenna (C-MSA) with U-shaped slot is used as a radiation element of the RL-MSAA. Radiation phase of the U-slot C-MSA is controlled by tuning the radius of the C-MSA and dimensions of the U-slot on the C-MSA; therefore, the desired phase distribution of the RL-MSAA can be realized. In this paper, a linearly polarized RL-MSAA with three concentric rows of C-MSAs at a spacing of 0.65 wavelengths is designed for 12GHz operation. In order to realize uniform phase distribution, the U-slot C-MSAs are arranged for inner two rows and normal C-MSAs are arranged for the termination row. Validity of the linearly polarized RL-MSAA with the U-slot C-MSAs for radiation phase control is demonstrated by simulation and measurement.

To enhance the throughput of wireless local area networks (WLANs) by efficiently utilizing the radio resource, a distributed coordination function-based (DCF-based) orthogonal frequency division multiple access (OFDMA) WLAN system has been proposed. In the system, since each OFDMA sub-channel is assigned to the associated station with the highest channel gain, the transmission rate of DATA frames can be enhanced thanks to multi-user diversity. However, the optimum allocation of OFDMA sub-channels requires the estimation of channel state information (CSI) of all associated stations, and this incurs excessive signaling overhead. As the number of associated stations increases, the signaling overhead severely degrades the throughput of DCF-based OFDMA WLAN. To reduce the signaling overhead while obtaining a sufficient diversity gain, this paper proposes a channel access scheme that performs multiple DCF-based channel access. The key idea of the proposed scheme is to introduce additional DCF-based prioritized access along with the traditional DCF-based random access. In the additional DCF-based prioritized access, by dynamically adjusting contention window size according to the CSI of each station, only the stations with better channel state inform their CSI to the access point (AP), and the signaling overhead can be reduced while maintaining high multi-user diversity gain. Numerical results confirm that the proposed channel access scheme enhances the throughput of OFDMA WLAN.

The applicability of at-speed scan-based logic built-in self-test (BIST) is being severely challenged by excessive capture power that may cause erroneous test responses even for good circuits. Different from conventional low-power BIST, this paper is the first to explicitly focus on achieving capture power safety with a novel and practical scheme, called capture-power-safe logic BIST (CPS-LBIST). The basic idea is to identify all possibly-erroneous test responses caused by excessive capture power and use the well-known approach of masking (bit-masking, slice-masking,vector-masking) to block them from reaching the multiple-input signature register(MISR). Experiments with large benchmark circuits and a large industrial circuit demonstrate that CPS-LBIST can achieve capture power safety with negligible impact on test quality and circuit overhead.

This paper deals with the problem of reconstructing a high-resolution digital image from a single low-resolution digital image and proposes a new intra-frame super-resolution algorithm based on the mixed lp/l1 norm minimization. Introducing some assumptions, this paper formulates the super-resolution problem as a mixed l0/l1 norm minimization and relaxes the l0 norm term to the lp norm to avoid ill-posedness. A heuristic iterative algorithm is proposed based on the iterative reweighted least squares (IRLS). Numerical examples show that the proposed algorithm achieves super-resolution efficiently.

In this letter, we propose an improved single image haze removal algorithm using image segmentation. It can effectively resolve two common problems of conventional algorithms which are based on dark channel prior: halo artifact and wrong estimation of atmospheric light. The process flow of our algorithm is as follows. First, the input hazy image is over-segmented. Then, the segmentation results are used for improving the conventional dark channel computation which uses fixed local patches. Also, the segmentation results are used for accurately estimating the atmospheric light. Finally, from the improved dark channel and atmospheric light, an accurate transmission map is computed allowing us to recover a high quality haze-free image.

In this paper, we consider multi-source multi-relay power allocation in cooperative wireless networks. A new intelligent optimization algorithm, multi-objective free search (MOFS), is proposed to efficiently allocate cooperative relay power to better support multiple sources transmission. The existence of Pareto optimal solutions is analyzed for the proposed multi-objective power allocation model when the objectives conflict with each other, and the MOFS algorithm is validated using several test functions and metrics taken from the standard literature on evolutionary multi-objective optimization. Simulation results show that the proposed scheme can effectively get the potential optimal solutions of multi-objective power allocation problem, and it can effectively optimize the tradeoff between network sum-rate and fairness in different applications by selection of the corresponding solution.

The large amounts of freely available open source software over the Internet are fundamentally changing the traditional paradigms of software development. Efficient categorization of the massive projects for retrieving relevant software is of vital importance for Internet-based software development such as solution searching, best practices learning and so on. Many previous works have been conducted on software categorization by mining source code or byte code, but were verified on only relatively small collections of projects with coarse-grained categories or clusters. However, Internet-based software development requires finer-grained, more scalable and language-independent categorization approaches. In this paper, we propose a novel approach to hierarchically categorize software projects based on their online profiles. We design a SVM-based categorization framework and adopt a weighted combination strategy to aggregate different types of profile attributes from multiple repositories. Different basic classification algorithms and feature selection techniques are employed and compared. Extensive experiments are carried out on more than 21,000 projects across five repositories. The results show that our approach achieves significant improvements by using weighted combination. Compared to the previous work, our approach presents competitive results with more finer-grained and multi-layered category hierarchy with more than 120 categories. Unlike approaches that use source code or byte code, our approach is more effective for large-scale and language-independent software categorization. In addition, experiments suggest that hierarchical categorization combined with general keyword-based searching improves the retrieval efficiency and accuracy.

In this paper, a new analog signal transmission technique called analog single-carrier transmission with frequency-domain equalization (analog SC-FDE) is proposed. Analog SC-FDE applies discrete Fourier transform (DFT), frequency-domain spectrum shaping and mapping, inverse DFT (IDFT), and cyclic prefix (CP) insertion before transmission. At the receiver, one-tap FDE is applied to take advantage of frequency diversity. This paper considers, as an example, analog voice transmission. A theoretical analysis of the normalized mean square error (NMSE) performance is carried out to evaluate the transmission property of the proposed analog SC-FDE and is confirmed by computer simulation. We show that analog SC-FDE achieves better NMSE performance than conventional analog signal transmission scheme.

The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amyotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. In this paper, we introduce the gaze estimation system of electrooculogram signals. Using this system, the electrooculogram signals can be recorded when the patients focused on each direct. All these recorded signals could be analyzed using math-method and the mathematical model will be set up. Gaze estimation can be recognized using electrooculogram signals follow these models.

Differential games are considered an extension of optimal control problems, which are used to formulate centralized control problems in smart grids. Optimal control theory is used to study systems consisting of one agent with one objective, whereas differential games are used to formulate systems consisting of multiple agents with multiple objectives. Therefore, a differential-game-theoretic approach is appropriate for formulating decentralized demand-side energy management systems where there are multiple decision-making entities interacting with each other. Moreover, in many smart grid applications, we need to obtain information for control via communication systems. To formulate the influence of communication availability, differential game theory is also promising because the availability of communication is considered as part of an information structure (i.e., feedback or open-loop) in differential games. The feedback information structure is adopted when information for control can be obtained, whereas the open-loop information structure is applied when the information cannot be obtained because of communication failure. This paper proposes a comprehensive framework for evaluating the performance of demand-side actors in a demand-side management system using each control scheme according to both communication availability and sampling frequency. Numerical analysis shows that the proposed comprehensive framework allows for an analysis of trade-off for decentralized and centralized control schemes.

This letter introduces a new reference frame to improve the performance of motion estimation and compensation in video coding, based on a video stabilization technique. The proposed method synthesizes the new reference frame from the previous frame in a way that the new reference and current frames have the same camera orientations. The overhead data for each frame to transmit from an encoder to a decoder is only three rotational angles along the x, y, and z axes. Since the new reference and current frames have the same camera orientations, the proposed method significantly improves the performance of motion estimation and compensation for video sequences having dynamic camera motion by up to 0.98 dB with negligible overhead data.

Local descriptors, Local Binary Pattern (LBP) and Scale Invariant Feature Transform (SIFT) are widely used in various computer applications. They emphasize different aspects of image contents. In this letter, we propose to combine them in sparse coding for categorizing scene images. First, we regularly extract LBP and SIFT features from training images. Then, corresponding to each feature, a visual word codebook is constructed. The obtained LBP and SIFT codebooks are used to create a two-dimensional table, in which each entry corresponds to an LBP visual word and a SIFT visual word. Given an input image, LBP and SIFT features extracted from the same positions of this image are encoded together based on sparse coding. After that, spatial max pooling is adopted to determine the image representation. Obtained image representations are converted into one-dimensional features and classified by utilizing SVM classifiers. Finally, we conduct extensive experiments on datasets of Scene Categories 8 and MIT 67 Indoor Scene to evaluate the proposed method. Obtained results demonstrate that combining features in the proposed manner is effective for scene categorization.

Feedback data loss can severely degrade overall system performance. In addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications that include different data traffic patterns. These data traffic patterns have wide varieties of diversities. To recover various traffic patterns we need to know the nature of their underlying property. In this paper, we propose a data recovery framework for different traffic patterns of CPS, which comprises data pre-processing step. In the proposed framework, we designed a Data Pattern Analyzer to classify the different patterns and built a model based on the pattern as a data pre-processing step. Inside the framework, we propose a data recovery scheme, called Efficient Temporal and Spatial Data Recovery (ETSDR) algorithm to recover the incomplete feedback for CPS to maintain real time control. In this algorithm, we utilize the temporal model based on the traffic pattern and consider the spatial correlation of the nearest neighbor sensors. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithms regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.

We proposed a method for estimating sound source positions in 3D space by integrating sound directions estimated by multiple microphone arrays and taking advantage of reflection information. Two types of sources with different directivity properties (human speech and loudspeaker speech) were evaluated for different positions and orientations. Experimental results showed the effectiveness of using reflection information, depending on the position and orientation of the sound sources relative to the array, walls, and the source type. The use of reflection information increased the source position detection rates by 10% on average and up to 60% for the best case.

In the traditional microphone array signal processing, the performance degrades rapidly when the array aperture decreases, which has been a barrier restricting its implementation in the small-scale acoustic system such as digital hearing aids. In this work a new compressed sampling method of miniature microphone array is proposed, which compresses information in the internal of ADC by means of mixture system of hardware circuit and software program in order to remove the redundancy of the different array element signals. The architecture of the method is developed using the Verilog language and has already been tested in the FPGA chip. Experiments of compressed sampling and reconstruction show the successful sparseness and reconstruction for speech sources. Owing to having avoided singularity problem of the correlation matrix of the miniature microphone array, when used in the direction of arrival (DOA) estimation in digital hearing aids, the proposed method has the advantage of higher resolution compared with the traditional GCC and MUSIC algorithms.