As the display resolution increases, an effective image upscaling technique is required for recent displays such as an ultra-high-definition display. Even though various image super-resolution algorithms have been developed for the image upscaling, they still do not provide the excellent performance in the ultra-high-definition display. This is because the texture creation capability in the algorithms is not sufficient. Hence, this paper proposes an efficient texture creation algorithm for enhancing the texture super-resolution performance. For the texture creation, we build a database with random patches in the off-line processing and we then synthesize fine textures by employing guided filter in the on-line real-time processing, based on the database. Experimental results show that the proposed texture creation algorithm provides sharper and finer textures compared with the existing state-of-the-art algorithms.

In this paper, we consider coded multi-input multi-output (MIMO) systems with low-density parity-check (LDPC) codes and space-time block code (STBC) in MIMO channels. The LDPC code takes the role of a channel code while the STBC provides spatial-temporal diversity. The performance of such coded MIMO system has been shown to be excellent in the past. In this paper, we present a performance analysis for an upper bound on probability of error for coded MIMO schemes. Compared to previous works, the proposed approach for the upper bound can avoid any explicit weight enumeration of codewords and provide a significant step for the upper bound by using a multinomial theorem. In addition, we propose a log domain convolution that enables us to handle huge numbers, e.g., 10500. Comparison of system simulations and numerical evaluations shows that the proposed upper bound is applicable for various coded MIMO systems.

Binary sparse representation based on arbitrary quality metrics and its applications are presented in this paper. The novelties of the proposed method are twofold. First, the proposed method newly derives sparse representation for which representation coefficients are binary values, and this enables selection of arbitrary image quality metrics. This new sparse representation can generate quality metric-independent subspaces with simplification of the calculation procedures. Second, visual saliency is used in the proposed method for pooling the quality values obtained for all of the parts within target images. This approach enables visually pleasant approximation of the target images more successfully. By introducing the above two novel approaches, successful image approximation considering human perception becomes feasible. Since the proposed method can provide lower-dimensional subspaces that are obtained by better image quality metrics, realization of several image reconstruction tasks can be expected. Experimental results showed high performance of the proposed method in terms of two image reconstruction tasks, image inpainting and super-resolution.

We developed and applied a new circuit, called the “Self-controllable Voltage Level (SVL)” circuit, not only to expand both “write” and “read” stabilities, but also to achieve a low stand-by power and data holding capability in a single low power supply, 90-nm, 2-kbit, six-transistor CMOS SRAM. The SVL circuit can adaptively lower and higher the word-line voltages for a “read” and “write” operation, respectively. It can also adaptively lower and higher the memory cell supply voltages for the “write” and “hold” operations, and “read” operation, respectively. This paper focuses on the “hold” characteristics and the standby power dissipations (PST) of the developed SRAM. The average PST of the developed SRAM is only 0.984µW, namely, 9.57% of that (10.28µW) of the conventional SRAM at a supply voltage (VDD) of 1.0V. The data hold margin of the developed SRAM is 0.1839V and that of the conventional SRAM is 0.343V at the supply voltage of 1.0V. An area overhead of the SVL circuit is only 1.383% of the conventional SRAM.

In this letter, a new semi-blind approach incorporating the bounded nature of communication sources with the distance between the equalizer outputs and the training sequence is proposed. By utilizing the sparsity property of l1-norm cost function, the proposed algorithm can outperform the semi-blind method based on higher-order statistics (HOS) criterion especially for transmitting sources with non-constant modulus. Experimental results demonstrate that the proposed method shows superior performance over the HOS based semi-blind method and the classical training-based method for QPSK and 16QAM sources equalization. While for 64QAM signal inputs, the proposed algorithm exhibits its superiority in low signal-to-noise-ratio (SNR) conditions compared with the training-based method.

Differential microphone arrays have been widely used in hands-free communication systems because of their frequency-invariant beampatterns, high directivity factors and small apertures. Considering the position of acoustic source always moving within a certain range in real application, this letter proposes an approach to construct the steerable first-order differential beampattern by using four omnidirectional microphones arranged in a non-orthogonal circular geometry. The theoretical analysis and simulation results show beampattern constructed via this method achieves the same direction factor (DF) as traditional DMAs and higher white noise gain (WNG) within a certain angular range. The simulation results also show the proposed method applies to processing speech signal. In experiments, we show the effectiveness and small computation amount of the proposed method.

Effective capacity (EC) is an important performance metric for a time-varying wireless channel in order to evaluate the communication rate in the physical layer (PHL) while satisfying the statistical delay quality of service (QoS) requirement in data-link layer (DLL). This paper analyzes EC of amplify-and-forward wireless relay network with different relay selection (RS) protocols. First, through the analysis of the probability density function (PDF) of received signal-to-noise ratio (SNR), the exact expressions of EC for direct transmission (DT), random relay (RR), random relay with direct transmission (RR-WDT), best relay (BR) protocols are derived. Then a novel best relay with direct transmission (BR-WDT) protocol is proposed to maximize EC and an exact expression of EC for BR-WDT protocol is developed. Simulations demonstrate that the derived analytical results well match those of Monte-Carlo simulations. The proposed BR-WDT protocol can always achieve larger EC than other protocols while guaranteeing the delay QoS requirement. Moreover, the influence of distance between source and relay on EC is discussed, and optimal relay position for different RS protocols is estimated. Furthermore, EC of all protocols becomes smaller while delay QoS exponent becomes larger, and EC of BR-WDT becomes better while the number of relays becomes larger.

This paper presents a water leakage monitoring system that gathers acoustic data of water pipes using wireless communication technology and identifies the sound of water leakage using machine leaning technology. To collect acoustic data effectively, this system combines three types of data-collection methods: drive-by, walk-by, and static. To design this system, it is important to ascertain the wireless communication distance that can be achieved with sensors installed in a basement. This paper also reports on radio propagation from underground manholes made from reinforced concrete and resin concrete in residential and commercial areas using the 920 MHz band. We reveal that it is possible to design a practical system that uses radio communication from underground sensors.

For more flexible and efficient use of radio spectrum, reconfigurable RF devices have important roles in the future wireless systems. In 5G mobile communications, concurrent multi-band operation using new SHF bands is considered. This paper presents a new configuration of dual-band SHF BPF consisting of a low SHF three-bit reconfigurable BPF and a high SHF BPF. The proposed dual-band BPF employs direct parallel connection without additional divider/combiner to reduce circuit elements and simplify the BPF. In order to obtain a good isolation between two passbands while achieving a wide center frequency range in the low SHF BPF, input/output impedances and external Qs of BPFs are analyzed and feedbacked to the design. A high SHF BPF design method with tapped transmission line resonators and lumped-element coupling is also presented to make the BPF compact. Two types of prototypes; all inductor-coupled dual-band BPF and C-L-C coupled dual-band BPF were designed and fabricated. Both prototypes have low SHF reconfigurable center frequency range from 3.5 to 5 GHz as well as high SHF center frequency of 8.5 GHz with insertion loss below 2.0 dB.

A wideband design of the waveguide short-slot 2-plane coupler with 2×2 input/output ports is designed, fabricated, and evaluated. Using coupling coefficients of complementary propagating modes which are TE11, TE21, and TE30 modes, the flatness of the output amplitudes of 2-plane coupler is improved. The coupler operates from 4.96GHz to 5.27GHz (bandwidth 6.1%) which is wider than the former coupler without considering the complementary propagating mode from 5.04GHz to 5.17GHz (bandwidth 2.5%).

In this letter, an effective low bit-rate image restoration method is proposed, in which image denoising and subspace regression learning are combined. The proposed framework has two parts: image main structure estimation by classical NLM denoising and texture component prediction by subspace joint regression learning. The local regression function are learned from denoised patch to original patch in each subspace, where the corresponding compression image patches are employed to generate anchoring points by the dictionary learning approach. Moreover, we extent Extreme Support Vector Regression (ESVR) as multi-variable nonlinear regression to get more robustness results. Experimental results demonstrate the proposed method achieves favorable performance compared with other leading methods.

Reproducing quadruped locomotion from an engineering viewpoint is important not only to control robot locomotion but also to clarify the nonlinear mechanism for switching between locomotion patterns. In this paper, we reproduced a quadruped locomotion pattern, gallop, using a central pattern generator (CPG) hardware network based on the abelian group Z4×Z2, originally proposed by Golubitsky et al. We have already used the network to generate three locomotion patterns, walk, trot, and bound, by controlling the voltage, EMLR, inputted to all CPGs which acts as a signal from the midbrain locomotor region (MLR). In order to generate the gallop and canter patterns, we first analyzed the network symmetry using group theory. Based on the results of the group theory analysis, we desymmetrized the contralateral couplings of the CPG network using a new parameter in addition to EMLR, because, whereas the walk, trot, and bound patterns were able to be generated from the spatio-temporal symmetry of the product group Z4×Z2, the gallop and canter patterns were not. As a result, using a constant element $hat{kappa}$ on Z2, the gallop and canter locomotion patterns were generated by the network on ${f Z}_4+hat{kappa}{f Z}_4$, and actually in this paper, the gallop locomotion pattern was generated on the actual circuit.

Attribute-based encryption (ABE), a cryptographic primitive, realizes fine-grained access control. Because of its attractive functionality, many systems based on ABE have been constructed to date. In such cryptographic systems, revocation functionality is indispensable to handle withdrawal of users, secret key exposure, and others. Although many ABE schemes with various functionalities have been proposed, only a few of these are revocable ABE (RABE). In this paper, we propose two generic constructions of RABE from ABE. Our first construction employs the pair encoding framework (Attrapadung, EUROCRYPT 2014), and combines identity-based revocation and ABE via the generic conjunctive conversion of Attrapadung and Yamada (CT-RSA 2015). Our second construction converts ABE to RABE directly when ABE supports Boolean formulae. Because our constructions preserve functionalities of the underlying ABE, we can instantiate various fully secure RABE schemes for the first time, e.g., supporting regular languages, with unbounded attribute size and policy structure, and with constant-size ciphertext and secret key.

A light field, which is often understood as a set of dense multi-view images, has been utilized in various 2D/3D applications. Efficient light field acquisition using a coded aperture camera is the target problem considered in this paper. Specifically, the entire light field, which consists of many images, should be reconstructed from only a few images that are captured through different aperture patterns. In previous work, this problem has often been discussed from the context of compressed sensing (CS), where sparse representations on a pre-trained dictionary or basis are explored to reconstruct the light field. In contrast, we formulated this problem from the perspective of principal component analysis (PCA) and non-negative matrix factorization (NMF), where only a small number of basis vectors are selected in advance based on the analysis of the training dataset. From this formulation, we derived optimal non-negative aperture patterns and a straight-forward reconstruction algorithm. Even though our method is based on conventional techniques, it has proven to be more accurate and much faster than a state-of-the-art CS-based method.

Both spatial diversity and multihop relaying are considered to be effective methods for mitigating the impact of atmospheric turbulence-induced fading on the performance of free-space optical (FSO) systems. Multihop relaying can significantly reduce the impact of fading by relaying the information over a number of shorter hops. However, it is not feasible or economical to deploy relays in many practical scenarios. Spatial diversity could substantially reduce the fading variance by introducing additional degrees of freedom in the spatial domain. Nevertheless, its superiority is diminished when the fading sub-channels are correlated. In this paper, our aim is to study the fundamental performance limits of spatial diversity suffering from correlated Gamma-Gamma (G-G) fading channels in multihop coherent FSO systems. For the performance analysis, we propose to approximate the sum of correlated G-G random variables (RVs) as a G-G RV, which is then verified by the Kolmogorov-Smirnov (KS) goodness-of-fit statistical test. Performance metrics, including the outage probability and the ergodic capacity, are newly derived in closed-form expressions and thoroughly investigated. Monte-Carlo (M-C) simulations are also performed to validate the analytical results.

In this paper, we improve upon the accuracy of existing tracklet generation methods by repairing tracklets based on their quality evaluation and detection propagation. Starting from object detections, we generate tracklets using three existing methods. Then we perform co-tracklet quality evaluation to score each tracklet and filtered out good tracklet based on their scores. A detection propagation method is designed to transfer the detections in the good tracklets to the bad ones so as to repair bad tracklets. The tracklet quality evaluation in our method is implemented by intra-tracklet detection consistency and inter-tracklet detection completeness. Two propagation methods; global propagation and local propagation are defined to achieve more accurate tracklet propagation. We demonstrate the effectiveness of the proposed method on the MOT 15 dataset

Computing the partition function of the Ising model on a graph has been investigated from both sides of computer science and statistical physics, with producing fertile results of P cases, FPTAS/FPRAS cases, inapproximability and intractability. Recently, measurement-based quantum computing as well as quantum annealing open up another bridge between two fields by relating a tree tensor network representing a quantum graph state to a rank decomposition of the graph. This paper makes this bridge wider in both directions. An $O^*(2^{ rac{omega}{2} bw(G)})$-time algorithm is developed for the partition function on n-vertex graph G with branch decomposition of width bw(G), where O* ignores a polynomial factor in n and ω is the matrix multiplication parameter less than 2.37287. Related algorithms of $O^*(4^{rw( ilde{G})})$ time for the tree tensor network are given which are of interest in quantum computation, given rank decomposition of a subdivided graph $ ilde{G}$ with width $rw( ilde{G})$. These algorithms are parameter-exponential, i.e., O*(cp) for constant c and parameter p, and such an algorithm is not known for a more general case of computing the Tutte polynomial in terms of bw(G) (the current best time is O*(min{2n, bw(G)O(bw(G))})) with a negative result in terms of the clique-width, related to the rank-width, under ETH.

This paper studies a variant of the graph partitioning problem, called the evacuation planning problem, which asks us to partition a target area, represented by a graph, into several regions so that each region contains exactly one shelter. Each region must be convex to reduce intersections of evacuation routes, the distance between each point to a shelter must be bounded so that inhabitants can quickly evacuate from a disaster, and the number of inhabitants assigned to each shelter must not exceed the capacity of the shelter. This paper formulates the convexity of connected components as a spanning shortest path forest for general graphs, and proposes a novel algorithm to tackle this multi-objective optimization problem. The algorithm not only obtains a single partition but also enumerates all partitions simultaneously satisfying the above complex constraints, which is difficult to be treated by existing algorithms, using zero-suppressed binary decision diagrams (ZDDs) as a compressed expression. The efficiency of the proposed algorithm is confirmed by the experiments using real-world map data. The results of the experiments show that the proposed algorithm can obtain hundreds of millions of partitions satisfying all the constraints for input graphs with a hundred of edges in a few minutes.

Given a graph G=(V,E) where V and E are a vertex and an edge set, respectively, specified with a subset VNT of vertices called a non-terminal set, the spanning tree with non-terminal set VNT is a connected and acyclic spanning subgraph of G that contains all the vertices of V where each vertex in a non-terminal set is not a leaf. The complexity of finding a spanning tree with non-terminal set VNT on general graphs where each edge has the weight of one is known to be NP-hard. In this paper, we show that if G is an interval graph then finding a spanning tree with a non-terminal set VNT of G is linearly-solvable when each edge has the weight of one.

Precession angle and precession period are significant parameters for identifying space micro-motion targets. To implement high-accuracy estimation of precession parameters without any prior knowledge about structure parameters of the target, a parameters extraction method based on HRRP sequences is proposed. The precession model of cone-shaped targets is established and analyzed firstly. Then the projection position of scattering centers on HRRP induced by precession is indicated to be approximate sinusoidal migration. Sequences of scattering centers are associated by sinusoid extraction algorithm. Precession angle and precession period are estimated utilizing error function optimization at last. Simulation results under various SNR levels based on electromagnetic calculation data demonstrate validity of the proposed method.