A planar circularly-polarized (CP) small antenna is proposed. To obtain a low profile configuration, a co-planar waveguide (CPW) structure is employed. Circular polarization is achieved using a curved stub that generates current distribution in a direction orthogonal to the current distribution from the patch. Using meander lines and a series gap capacitance, a 70% size reduction is achieved compared to a half-wavelength resonant antenna. To the best of the authors' knowledge, the proposed antenna is the smallest CP antenna using CPW technology. The measured 3 dB axial ratio bandwidth is 8.3% from 3.83 GHz to 4.16 GHz, and a 1.6 dBic gain and 89% efficiency are achieved.

We propose an active noise control (ANC) system for reducing periodic noise generated in a high magnetic field such as noise generated from magnetic resonance imaging (MRI) devices (MR noise). The proposed ANC system utilizes optical microphones and piezoelectric loudspeakers, because specific acoustic equipment is required to overcome the high-field problem, and consists of a head-mounted structure to control noise near the user's ears and to compensate for the low output of the piezoelectric loudspeaker. Moreover, internal model control (IMC)-based feedback ANC is employed because the MR noise includes some periodic components and is predictable. Our experimental results demonstrate that the proposed ANC system (head-mounted structure) can significantly reduce MR noise by approximately 30 dB in a high field in an actual MRI room even if the imaging mode changes frequently.

In view of the frequent and complex changes of GNSS visible satellite constellation in attitude determination system, an improved attitude signal simulation algorithm for high dynamic satellite signal simulator is proposed. Based on Software Radio architecture, elevation calculation in the antenna coordinate system and channel state control logic under the condition of carrier attitude changes are introduced into the algorithm to implement synchronous scheduling of visible satellite constellation and attitude signal simulation. This work guarantees the simulator to run constantly and stably for a long time with the advantages of high precision and low complexity. Compared with synchronous positioning results from the receiver, the simulation results show that not only can the output signals of the simulator accurately reflect the carrier's attitude characteristics, but also no step error is generated and the positioning precision is not influenced when visible satellite constellation changes.

A translucent wavelength switched optical network (WSON) is a cost-efficient infrastructure between opaque networks and transparent optical networks, which aims at seeking a graceful balance between network cost and service provisioning performance. In this paper, we experimentally present a resilient translucent WSON with the control of an enhanced path computation element (PCE) and extended generalized multi-protocol label switching (GMPLS) controllers. An adaptive routing and wavelength assignment scheme with the consideration of accumulated physical impairments, wavelength availabilities and regenerator allocation is experimentally demonstrated and evaluated for dynamic provisioning of lightpaths. By using two different network scenarios, we experimentally verify the feasibility of the proposed solutions in support of translucent WSON, and quantitatively evaluate the path computation latency, network blocking probability and service disruption time during end-to-end lightpath restoration. We also deeply analyze the experimental results and discuss the synchronization between the PCE and the network status. To the best of our knowledge, the most significant progress and contribution of this paper is that, for the first time, all the proposed methodologies in support of PCE/GMPLS controlled translucent WSON, including protocol extensions and related algorithms, are implemented in a network testbed and experimentally evaluated in detail, which allows verifying their feasibility and effectiveness when being potentially deployed into real translucent WSON.

For the 3D face recognition numerous methods have been proposed, but little attention has been given to the local-based representation for the texture map of the 3D models. In this paper, we propose a novel 3D face recognition approach based on locally extracted Geodesic Pseudo Zernike Moment Array (GPZMA) of the texture map when only one exemplar per person is available. In the proposed method, the function of the PZM is controlled by the geodesic deformations to tackle the problem of face recognition under the expression and pose variations. The feasibility and effectiveness investigation for the proposed method is conducted through a wide range of experiments using publicly available BU-3DFE and Bosphorus databases including samples with different expression and pose variations. The performance of the proposed method is compared with the performance of three state-of-the-art benchmark approaches. The encouraging experimental results demonstrate that the proposed method achieves much higher accuracy than the benchmarks in single-model databases.

This paper proposes a new sine wave approximation method for the PAC of DDFS. Sine wave is approximated by removing the harmonic components from trapezoid waveform. Experimental results show that the proposed PAC is advantageous in the SFDR range less than 60 dBc due to its small hardware cost.

An algorithm for estimating sinusoidal parameters is presented. In this paper, it is assumed that an observed signal is a single sinusoidal signal contaminated by white Gaussian noise. Based on this assumption, the sinusoidal parameters can be found by minimizing a cost function using the mean squared error (MSE) between the observed signal and a sinusoidal signal with arbitrary sinusoidal parameters. Because the cost function is nonlinear and not convex, it has undesirable local minima. To solve the minimization problem, we propose to use the roots of an algebraic equation. The algebraic equation is derived straightforwardly from the cost function. We show that the global solution is formulated by using the roots of the algebraic equation.

The present paper introduces a new approach to the construction of a sequence set with a zero-correlation zone for both periodic and aperiodic correlation functions. The proposed sequences can be constructed from a pair of Hadamard matrices of orders n0 and n1. The constructed sequence set consists of n0 n1 ternary sequences, each of length n0(m+2)(n1+Δ), for a non-negative integer m and Δ ≥ 2. The zero-correlation zone of the proposed sequences is |τ| ≤ n0m+1-1, where τ is the phase shift. The proposed sequence set consists of n0 subsets, each with a member size n1. The correlation function of the sequences of a pair of different subsets, referred to as the inter-subset correlation function, has a zero-correlation zone with a width that is approximately Δ times that of the correlation function of sequences of the same subset (intra-subset correlation function). The inter-subset zero-correlation zone of the proposed sequences is |τ| ≤ Δn0m+1, where τ is the phase shift. The wide inter-subset zero-correlation enables performance improvement during application of the proposed sequence set.

These days, cheap and intelligent sensors, networked through wireless links and deployed in large numbers, provide unprecedented opportunities for monitoring and controlling homes, cities and the environment. Networked sensors also offer a broad range of applications. Localization capability is essential in most wireless sensor networks applications; for instance in environmental monitoring applications such as animal habitat monitoring, bush fire surveillance, water quality monitoring and precision agriculture, the measurement data are meaningless without accurate knowledge of where they are obtained. Localization techniques are used to determine location information by estimating the location of each sensor node. Distance measurement errors are commonly known to affect the accuracy of the estimated location; resulting in errors that may be due to inherent or environmental factors. Trilateration [1] is a well-known method for localizing nodes by using the distances to three anchor nodes; yet it performs poorly when they are many distance measurement errors. Therefore, we propose the LRD (Localization with Ratio-Distance) algorithm, which performs strongly even in the presence of many measurement errors associated with the estimated distance to anchor nodes. Simulations using the OPNET Modeler show that LRD is more accurate than trilateration.

This paper defines a Quality of Experience (QoE) parameter for multi-view video streaming service over Wireless Broadband Internet, and proposes cross-layer optimization (CLO) algorithm to maximize the QoE. The proposed CLO algorithm interacts with all layers from PHY layer to video layer. Under the time-varying wireless channel condition, it guarantees service continuity to the user by selecting frames to be transmitted. The CLO technique takes inter-view and the temporal significance of the multi-view video frames into consideration when deciding the Transmission Frame Set (TFS) and its Levels of FEC (LOF). Through simulation of the proposed technique, it is shown that the optimal quality of the multi-view video can be achieved even during hand-over, using the minimum amount of resources. Visual quality of multi-view video streams is improved by about 15.330.2%, especially up to 39.165% during the hand-over. Moreover, continuity of the most important view has been increased by 20.139.1% in comparison with conventional method.

Nearest neighbor search (NNS) among large-scale and high-dimensional vectors plays an important role in recent large-scale multimedia search applications. This paper proposes an optimized multiple codebook construction method for an approximate NNS scheme based on product quantization, where sets of residual sub-vectors are clustered according to their distribution and the codebooks for product quantization are constructed from these clusters. Our approach enables us to adaptively select the number of codebooks to be used by trading between the search accuracy and the amount of memory available.

A novel predistortion technique using an automatic average-power bias controlled diode is proposed to compensate the complicated nonlinear characteristics of a microwave class-F power amplifier using an AlGaN/GaN HEMT. The optimum value for diode bias voltage is automatically set according to detected input average RF power level. A high-efficiency 1.9 GHz class-F GaN HEMT power amplifier with the automatic average-power bias control (ABC) diode linearizer achieves an improved third order inter-modulation distortion (IMD3) of better than -45 dBc at a smaller than 6 dB output power back-off from a saturated output power of 27 dBm, without changing drain efficiency. The adjacent channel leakage power ratio (ACPR) for 1.9 GHz W-CDMA signals is below -40 dBc at output power levels of smaller than 20 dBm for the class-F power amplifier.

We propose an improved TDoA (Time Difference of Arrival) localization scheme based on PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: the re-estimation of TDoA parameters and the re-localization of tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. Simulation results show that the proposed scheme achieves better location performance than the traditional TDoA localization in various channel environments.

The detection of object categories with large variations in appearance is a fundamental problem in computer vision. The appearance of object categories can change due to intra-class variations, background clutter, and changes in viewpoint and illumination. For object categories with large appearance changes, some kind of sub-categorization based approach is necessary. This paper proposes a sub-category optimization approach that automatically divides an object category into an appropriate number of sub-categories based on appearance variations. Instead of using predefined intra-category sub-categorization based on domain knowledge or validation datasets, we divide the sample space by unsupervised clustering using discriminative image features. We then use a cluster performance analysis (CPA) algorithm to verify the performance of the unsupervised approach. The CPA algorithm uses two performance metrics to determine the optimal number of sub-categories per object category. Furthermore, we employ the optimal sub-category representation as the basis and a supervised multi-category detection system with χ2 merging kernel function to efficiently detect and localize object categories within an image. Extensive experimental results are shown using a standard and the authors' own databases. The comparison results reveal that our approach outperforms the state-of-the-art methods.

In this letter we present efficient iterative frequency domain equalization for single-carrier (SC) transmission systems with insufficient cyclic prefix (CP). Based on minimum mean square error (MMSE) criteria, iterative decision feedback frequency domain equalization (IDF-FDE) combined with cyclic prefix reconstruction (CPR) is derived to mitigate inter-symbol interference (ISI) and inter-carrier interference (ICI). Computer simulation results reveal that the proposed scheme significantly improves the performance of SC systems with insufficient CP compared with previous schemes.

The development of the electricity market enables us to provide electricity of varied quality and price in order to fulfill power consumers' needs. Such customers choices should influence the process of adjusting power generation and spinning reserve, and, as a result, change the structure of a unit commitment optimization problem (UCP). To build a unit commitment model that considers customer choices, we employ fuzzy variables in this study to better characterize customer requirements and forecasted future power loads. To measure system reliability and determine the schedule of real power generation and spinning reserve, fuzzy Value-at-Risk (VaR) is utilized in building the model, which evaluates the peak values of power demands under given confidence levels. Based on the information obtained using fuzzy VaR, we proposed a heuristic algorithm called local convergence-averse binary particle swarm optimization (LCA-PSO) to solve the UCP. The proposed model and algorithm are used to analyze several test systems. Comparisons between the proposed algorithm and the conventional approaches show that the LCA-PSO performs better in finding the optimal solutions.

We propose a polarization-multiplexing QPSK modulator for synthesis of a 16 QAM signal. The generation mechanism of 16 QAM is based on an electro-optic vector digital-to-analog converter, which can generate optical multilevel signals from binary electric data sequences. A quad-parallel Mach-Zehnder modulator (QPMZM) used in our previous research requires precise control of electric signals or fabrication of a variable optical attenuator, which significantly raises the degree of difficulty to control electric signals or device fabrication. To overcome this difficulty, we developed the polarization-multiplexing QPSK modulator, which improved the method of superposition of QPSK signals. In the polarization-multiplexing QPSK modulator, two QPSK signals are output with orthogonal polarization and superposed through a polarizer. The amplitude ratio between the two QPSK signals can be precisely controlled by rotating the polarizer to arrange the 16 symbols equally. Generation of 16 QAM with 40 Gb/s and a bit error rate of 5.6910-5 was successfully demonstrated using the polarization-multiplexing QPSK modulator. This modulator has simpler configuration than the previous one, utilized a dual-polarization MZM, alleviating complicated control of electric signals.

This paper studies the design of Cascade Granular Neural Networks (CGNN) for human-centric systems. In contrast to typical rule-based systems encountered in fuzzy modeling, the proposed method consists of two-phase development for CGNN. First, we construct a Granular Neural Network (GNN) which could be treated as a preliminary design. Next, all modeling discrepancies are compensated by a second GNN with a collection of rules that become attached to the regions of the input space where the error is localized. These granular networks are constructed by building a collection of user-centric information granules through Context-based Fuzzy c-Means (CFCM) clustering. Finally, the experimental results on two examples reveal that the proposed approach shows good performance in comparison with the previous works.

Two designs of wideband compact MIMO antenna using printed dipoles are proposed in this paper. One is a three-port orthogonal polarization antenna and the other is a cube-six-port antenna. Measured results for the antennas show that they resonate at 2.6 GHz and support a bandwidth of over 400 MHz. The worst mutual coupling for the three-port orthogonal polarization antenna is kept under -20 dB whereas that level of the cube-six-port antenna is -18 dB. A number of experiments are conducted on MIMO systems with these compact antennas and linear antenna arrays. Measured data are analyzed to examine channel characteristics, such as cumulative distribution functions (CDFs) of eigenvalues. Furthermore, the effect of different antenna configurations on channel capacity is highlighted and discussed. A high data rate capacity can be achieved with the compact antennas, particularly from the cube-six-port variant. These antennas might be applied in actual MIMO systems in wireless communications.

In this letter, we propose an effective preamble based on constant amplitude and zero auto-correlation (CAZAC) sequence for multi-input multi-output (MIMO) and cooperative WiMedia ultra-wideband (UWB) systems. The proposed preamble even provides better single-channel estimation performance than the preamble specified in the standard in severe UWB channel model. The effectiveness of the proposed design is confirmed through the mean square error (MSE) performance.