This paper discusses the infinite horizon static output feedback stochastic Nash games involving state-dependent noise in weakly coupled large-scale systems. In order to construct the strategy, the conditions for the existence of equilibria have been derived from the solutions of the sets of cross-coupled stochastic algebraic Riccati equations (CSAREs). After establishing the asymptotic structure along with the positive semidefiniteness for the solutions of CSAREs, recursive algorithm for solving CSAREs is derived. As a result, it is shown that the proposed algorithm attains the reduced-order computations and the reduction of the CPU time. As another important contribution, the uniqueness of the strategy set is proved for the sufficiently small parameter ε. Finally, in order to demonstrate the efficiency of the proposed algorithm, numerical example is given.

Point Pattern Matching (PPM) is an essential problem in many image analysis and computer vision tasks. This paper presents a two-stage algorithm for PPM problem using ellipse fitting and dual Hilbert scans. In the first matching stage, transformation parameters are coarsely estimated by using four node points of ellipses which are fitted by Weighted Least Square Fitting (WLSF). Then, Hilbert scans are used in two aspects of the second matching stage: it is applied to the similarity measure and it is also used for search space reduction. The similarity measure named Hilbert Scanning Distance (HSD) can be computed fast by converting the 2-D coordinates of 2-D points into 1-D space information using Hilbert scan. On the other hand, the N-D search space can be converted to a 1-D search space sequence by N-D Hilbert Scan and an efficient search strategy is proposed on the 1-D search space sequence. In the experiments, we use both simulated point set data and real fingerprint images to evaluate the performance of our algorithm, and our algorithm gives satisfying results both in accuracy and efficiency.

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

This letter studies the tracking error in Multi-input Multi-output Feedback Error Learning (MIMO-FEL) system having insufficient excitation. It is shown that the error converges to zero exponentially even if the reference signal lacks the persistently excitation (PE) condition. Furthermore, by making full use of this fast convergence, we estimate the plant parameter while in operation based on frequency response. Simulation results show the effectiveness of the proposed method compared to a conventional approach.

The frequency domain binaural model (FDBM) has been previously proposed to localize multiple sound sources. Since the method requires only two input signals and uses interaural phase and level differences caused by the diffraction generated by the head, flexibility in application is very high when the head is considered as an object. When an object is symmetric with respect to the two microphones, the performance of sound source localization is degraded, as a human being has front-back confusion due to the symmetry in a median plane. This paper proposes to reduce the degradation of performance on sound source localization by a combination of the microphone pair outputs using the FDBM. The proposed method is evaluated by applying to a security camera system, and the results showed performance improvement in sound source localization because of reducing the number of cones of confusion.

Under the assumption that the clock can be inputted to each register at an arbitrary timing, the minimum feasible clock period might be reduced by register relocation while maintaining the circuit behavior and topology. However, if the minimum feasible clock period is reduced, then the number of registers tends to be increased. In this paper, we propose a gate-level register relocation method that reduces the number of registers while keeping the target clock period. In experiments, the proposed method reduces the number of registers in the practical time in most circuits.

This paper proposes a novel chaotic multiple-bits modulation scheme that uses the parameters in the map as data carrier for chaotic digital communication. Chaotic signals modulated with the parameters corresponding to the information to be transmitted are sent to the receiver. The information sent to the receiver can be decoded by a correlation detector. This scheme can increase the number of transmittable information bit per unit carrier signals by increasing the number of mapping parameters to be used for modulation. We verify the performance of this scheme using bit error rate (BER) through computer simulation. Also, we compare the performance of the proposed method with a conventional single-bit modulation scheme.

An image sensor for a use of colorimeter is characterized based on the CIE standard colorimetric observer. We use the method of least squares to derive a colorimetric characterization matrix between RGB output signals and CIE XYZ tristimulus values. This paper proposes an adaptive measuring method to obtain the chromaticity of colored scenes and illumination through a 33 camera transfer matrix under a certain illuminant. Camera RGB outputs, sensor status values, and photoelectric characteristic are used to obtain the chromaticity. Experimental results show that the proposed method is valid in the measuring performance.

The problem of designing a robust adaptive control for nonlinear systems with uncertain time-varying parameters is addressed. The upper bound of uncertain parameters, considered even in control coefficients, are not required to be known. An adaptive tracking controller is presented and, using the Lyapunov theory, the closed-loop stability and tracking error convergence is shown. In order to improve the performance of the method, a robust mechanism is incorporated into the adaptive controller yielding a robust adaptive algorithm. The proposed controller guarantees the boundedness of all closed-loop signals and robust convergence of tracking error in spite of time-varying parameter uncertainties with unknown bounds. The parametric uncertain systems under consideration describes a wide class of nonlinear circuits and systems. As an application, a novel parametric model is derived for nonlinear Chua's circuit and then, the proposed method is used for its control. The effectiveness of the method is demonstrated by some simulation results.

Break arcs are generated in a DC 42 V-10 A resistive circuit. The contact material is Ag or Ag/ZnO. The number of break operations is two hundreds for each contact material. The motion of break arcs is observed with a high-speed camera. Relationship between the dependence of arc duration on the number of operations and the motion of arc spots is investigated. The following results are shown. For Ag contacts the arc duration is almost constant independent to the number of break operations. For Ag/ZnO contacts, on the other hand, the arc duration changes irregularly to short (59 ms) or long (69 ms) arc-duration after 30th break operation. The moving range of arc spots on contact surfaces is broad for the case of short arc-duration and is narrow for the case of long arc-duration. The cause of the results for Ag/ZnO contacts is considered that the difference of the boiling points of Ag and ZnO leads to the porous structure on the contact surface.

The key to high performance in video coding lies on efficiently reducing the temporal redundancies. For this purpose, H.264/AVC coding standard has adopted variable block size motion estimation on multiple reference frames to improve the coding gain. However, the computational complexity of motion estimation is also increased in proportion to the product of the reference frame number and the intermode number. The mathematical analysis in this paper reveals that the prediction errors mainly depend on the image edge gradient amplitude and quantization parameter. Consequently, this paper proposes the image content based early termination algorithm, which outperforms the original method adopted by JVT reference software, especially at high and moderate bit rates. In light of rate-distortion theory, this paper also relates the homogeneity of image to the quantization parameter. For the homogenous block, its search computation for futile reference frames and intermodes can be efficiently discarded. Therefore, the computation saving performance increases with the value of quantization parameter. These content based fast algorithms were integrated with Unsymmetrical-cross Multihexagon-grid Search (UMHexagonS) algorithm to demonstrate their performance. Compared to the original UMHexagonS fast matching algorithm, 26.14-54.97% search time can be saved with an average of 0.0369 dB coding quality degradation.

Introducing multi-agent (MA) technology into a SCADA (Supervisory Control and Data Acquisition) system can improve the serviceability and enhance maintenance-free operation with the inter-terminal parameter (ITP) method. In addition, the system's distributed intelligent field terminals (IFTs) use a common algorithm that is unaffected by any changes to the system specifications. As a result of these innovations, the proposed system has much better serviceability because it is much easier to make modifications compared to that of conventional systems. This system has been implemented for practical purposes at over 60 sites.

In this paper, we present a reconfigurable processor infrastructure to accelerate Java applications, called Jaguar. The Jaguar infrastructure consists of a compiler framework and a runtime environment support. The compiler framework selects a group of Java methods to be translated into hardware for delivering the best performance under limited resources, and translates the selected Java methods into Verilog synthesizable code modules. The runtime environment support includes the Java virtual machine (JVM) running on a host processor to provide Java execution environment to the generated Java accelerator through communication interface units while preserving Java semantics. Our compiler infrastructure is a tightly integrated and solid compiler-aided solution for Java reconfigurable computing. There is no limitation in generating synthesizable Verilog modules from any Java application while preserving Java semantics. In terms of performance, our infrastructure achieves the speedup by 5.4 times on average and by up to 9.4 times in measured benchmarks with respect to JVM-only execution. Furthermore, two optimization schemes such as an instruction folding and a live buffer removal can reduce 24% on average and up to 39% of the resource consumption.

Recently, many application systems have been developed by using a large number of cameras. If 3D points are observed from synchronized cameras, the multiple view geometry of these cameras can be computed and the 3D reconstruction of the scene is available. Thus, the synchronization of multiple cameras is essential. In this paper, we propose a method for synchronizing multiple cameras and for computing the epipolar geometry from uncalibrated and unsynchronized cameras. In particular we using affine invariance to match the frame numbers of camera images for finding the synchronization. The proposed method is tested by using real image sequences taken from uncalibrated and unsynchronized cameras.

Compared with previous standards, H.264/AVC adopts variable block size motion estimation (VBSME) and multiple reference frames (MRF) to improve the video quality. Full search motion estimation algorithm (FS), which calculates every search candidate in the search window for 7 block type with multiple reference frames, consumes massive computation power. Mathematical analysis reveals that the aliasing problem of subsampling algorithm comes from high frequency signal components. Moreover, high frequency signal components are also the main issues that make MRF algorithm essential. As we know, a picture being rich of texture must contain lots of high frequency signals. So based on these mathematical investigations, two fast VBSME algorithms are proposed in this paper, namely edge block detection based subsampling method and motion vector based MRF early termination algorithm. Experiments show that strong correlation exists among the motion vectors of those blocks belonging to the same macroblock. Through exploiting this feature, a dynamically adjustment of the search ranges of integer motion estimation is proposed in this paper. Combing our proposed algorithms with UMHS almost saves 96-98% Integer Motion Estimation (IME) time compared to the exhaustive search algorithm. The induced coding quality loss is less than 0.8% bitrate increase or 0.04 dB PSNR decline on average.

Motion of break arcs driven by external magnetic field is observed using a high-speed camera. The magnetic field is applied with a permanent magnet. Experimental circuit is DC42 V-10 A resistive circuit. Material of electrical contacts is silver. Following results are shown. The break arcs are driven in the direction according to Lorentz force. The arc duration decreases with decrease of the distance between the electrical contacts and the magnet. When the external magnetic-flux density at the position of the break arc is lower than a certain value, the effect of the magnetic field to drive the break arc becomes ineffective to shorten the arc duration. The result is explained with a relationship between the motion of break arc and the distribution of the external magnetic field.

Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coincides with the conditional rate-distortion function. In this paper, we extend the problem to the coding of multivariate Gaussian source with multiple Gaussian side information at the decoder. The achievable region is obtained, and it is easily extended to the case that the difference between the source and the side information is multivariate Gaussian, no matter what distributions the source and the side information are. We apply this theoretical model to Distributed Video Coding (DVC) by considering the difference of the Distributed frame (D frame) and the Side-information frame (S frame) to be multivariate Gaussian distributed. This introduces rate allocation problem into DVC, which can be solved by a reverse water-filling method. Simulation results show that around 1.5-2 dB coding gain benefits from the multivariate Gaussian Wyner-Ziv coding model.

In this paper, we present a robust small-object detection method, which we call "Frequency Pattern Emphasis Subtraction (FPES)", for wide-area surveillance such as that of harbors, rivers, and plant premises. For achieving robust detection under changes in environmental conditions, such as illuminance level, weather, and camera vibration, our method distinguishes target objects from background and noise based on the differences in frequency components between them. The evaluation results demonstrate that our method detected more than 95% of target objects in the images of large surveillance areas ranging from 30-75 meters at their center.

H∞ optimal control is one of the most successful achievements in the post modern control theory. In the H∞ optimal control, we design a controller that minimizes the H∞ norm of a given system. Although the algorithms to solve the problem have already been reported, they focus on numerical systems (systems without any unknown parameters) and, can not be applied for parametric systems (systems with unknown parameters). Given a parametric system, this paper presents an algorithm to compute the optimal H∞ norm of the system achieved by an output feedback controller. The optimal H∞ norm is expressed as , where φ(k) denotes a root of a bivariate polynomial. A numerical example is given to show the effectiveness of the algorithm.

In this paper, we propose a novel solution to improving wireless channel quality of wireless local area networks (WLANs) in fast-mobile environments, which uses a media-access-control (MAC) layer approach: adaptive frame-length control and block acknowledgement (ACK). In fast-mobile environments, using short frame lengths can suppress channel estimation error and decrease frame errors. However, it increases the MAC overhead, resulting in decreased throughput. To solve this tradeoff, we combined block ACK, which is specified in IEEE802.11e as an optional function, with adaptive frame-length control. Although adaptive frame-length control considering this tradeoff has previously been investigated, the targets were different from WLANs using orthogonal frequency division multiplexing (OFDM) in fast-mobile environments. The MAC-overhead reduction using block ACK is suitable for our frame-length control because it does not change the frame format in the physical layer. Also, it is a new idea to use block ACK as a solution to improving channel quality in fast-mobile environments. In this paper, we evaluate our method through computer simulations and verify the effectiveness of adaptive frame-length control that can accommodate relative speeds.