The hybrid antenna consisted of cylindrical dielectric resonator and rectangular slot was implemented. The hybrid antenna resonated at two different frequencies. The lower resonant frequency was associated with the rectangular slot while the higher resonant frequency was associated with the cylindrical dielectric resonator. Parametric investigation was carried out using simulation software. The proposed hybrid antenna had good agreement between the simulation and measurement results. A 24% bandwidth (return loss < 10 dB) of 2.30 GHz, and a 18% bandwidth (return loss < 10 dB) of 5.46 GHz was implemented successfully for application in ISM and UNII band.

Kernel logistic regression (KLR) is a powerful and flexible classification algorithm, which possesses an ability to provide the confidence of class prediction. However, its training--typically carried out by (quasi-)Newton methods--is rather time-consuming. In this paper, we propose an alternative probabilistic classification algorithm called Least-Squares Probabilistic Classifier (LSPC). KLR models the class-posterior probability by the log-linear combination of kernel functions and its parameters are learned by (regularized) maximum likelihood. In contrast, LSPC employs the linear combination of kernel functions and its parameters are learned by regularized least-squares fitting of the true class-posterior probability. Thanks to this linear regularized least-squares formulation, the solution of LSPC can be computed analytically just by solving a regularized system of linear equations in a class-wise manner. Thus LSPC is computationally very efficient and numerically stable. Through experiments, we show that the computation time of LSPC is faster than that of KLR by two orders of magnitude, with comparable classification accuracy.

An FFT-based full-search block matching algorithm (BMA) is described that uses the sum of squared differences (SSD) criterion. The proposed method does not have to extend a real signal into complex one. This reduces the computational load of FFT approaches. In addition, if two macroblocks share the same search window, they can be matched at the same time. In a simulation of motion estimation, the proposed method achieved the same performance as a direct SSD full search and its processing speed is faster than other FFT-based BMAs.

This article presents a unified analytical framework to evaluate the bit error probability (BEP) of M-QAM, R-QAM and M-PAM modulation schemes for different types of fading channels, modeled with Hoyt, Rice, Rayleigh, Nakagami and Log-normal distributions. The mathematical development is obtained for maximal-ratio combining multichannel reception and assumes independent fading paths. The new BEP expressions are written in terms of the integral of the moment generating funcion of the instantaneos signal-to-noise ratio. The advantage of this approach is that it can be applied to any type of fading, and the integrals, even though they do not provide exact expressions, can be numerically evaluated.

This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.

Threshold testing, which is an LSI testing method based on the acceptability of faults, is effective in yield enhancement of LSIs and selective hardening for LSI systems. In this paper, we propose test generation models for threshold test generation. Using the proposed models, we can efficiently identify acceptable faults and generate test patterns for unacceptable faults with a general test generation algorithm, i.e., without a test generation algorithm specialized for threshold testing. Experimental results show that our approach is, in practice, effective.

This letter presents results showing improved field uniformity in a reverberation chamber using quadratic residue diffusers. The optimal occupying ratio of the diffusers on one side wall of the chamber is presented. A reverberation chamber is an alternative to the semi-anechoic chamber, which is widely used for the analysis and measurement of electromagnetic interference and immunity. To analyze the field characteristics, quadratic residue diffusers were designed for the 1-3 GHz frequency band, and the FDTD method was used. At 1-3 GHz, the standard deviation of the test volume in the reverberation chamber was investigated. The reverberation chamber had good field uniformity when quadratic residue diffusers occupy 37.5-50% of one side wall of the reverberation chamber; the field uniformity saturated at the diffuser occupancy rate of 75%.

Estimating the number of signals (NIS) is an important goal in array signal processing, such as direction-of-arrival (DOA) estimation. A common approach for solving this problem is to use an eigenvalue of the array covariance matrix and information criterion, such as the Akaike information criterion (AIC) and minimum description length (MDL). However they suffer serious degradation, when the incoming signals are coherent. To estimate the NIS of the coherent signals impinging on a uniform linear array (ULA), a method for estimating the number of signals without eigendecomposition (MENSE) is proposed. The accuracy of the NIS estimation performance of MENSE is superior to the other algorithms equipped with preprocessing such as the spatial smoothing preprocessing (SSP) and forward/backward spatial smoothing techniques (FBSS) to decorrelate the coherency of signals. Instead of using SSP or FBSS preprocessing, MENSE uses the Hankel correlation matrices. The Hankel correlation matrices can not only decorrelate the coherency of signals but also suppress the influence of noise. However, in severe conditions like low signal-to-noise ratio (SNR) or a closely spaced signals impinging on a ULA, the NIS estimation metric of MENSE has some bias which causes estimation error. In this paper, we pay attention to the multiplicity defined by the ratio of the geometric mean to the arithmetic mean. Accordingly, we propose a new estimation metric that has less bias than that in MENSE. The Computer simulation results show that the proposed method is superior to MENSE in the above severe conditions.

Estimating the ratio of two probability density functions (a.k.a. the importance) has recently gathered a great deal of attention since importance estimators can be used for solving various machine learning and data mining problems. In this paper, we propose a new importance estimation method using a mixture of probabilistic principal component analyzers. The proposed method is more flexible than existing approaches, and is expected to work well when the target importance function is correlated and rank-deficient. Through experiments, we illustrate the validity of the proposed approach.

A compact antenna is proposed for operating at the Federal Communications Commission allocated ultra-wideband (UWB) of 3.1-10.6 GHz. The antenna is made by deforming a film antenna which consists of two glass-shaped and square-shaped radiation elements. The antenna in its planar form is optimized for the UWB operation and is deformed by different manners such as folding, meandering or twisting, without much influence on its input characteristics. The deformations not only miniaturize the antenna but also improve its radiation characteristics. A prototype with a dimension of 2033 mm2 is fabricated and then the antenna is deformed by rolling it into a circular rod with a diameter of 6.4 mm, or meandering it into a square rod with a cross-sectional dimension of 65 mm2. The deformed antennas maintain the operation at the UWB and have better omni-directional radiation patterns than the antenna in its planar form.

This paper presents a combined feature extraction method to improve the performance of bag-of-features image classification. We apply 10 relevant operations to global/local statistics of visual words. Because the pairwise combination of visual words is large, we apply feature selection methods including fisher discriminant criterion and L1-SVM. The effectiveness of the proposed method is confirmed through the experiment.

This paper presents an approach for improving proximity and diversity in multiobjective evolutionary algorithms (MOEAs). The idea is to discover new nondominated solutions in the promising area of search space. It can be achieved by applying mutation only to the most converged and the least crowded individuals. In other words, the proximity and diversity can be improved because new nondominated solutions are found in the vicinity of the individuals highly converged and less crowded. Empirical results on multiobjective knapsack problems (MKPs) demonstrate that the proposed approach discovers a set of nondominated solutions much closer to the global Pareto front while maintaining a better distribution of the solutions.

For optimization problems with irregular and complex multimodal landscapes, Estimation of Distribution Algorithms (EDAs) suffer from the drawback of premature convergence similar to other evolutionary algorithms. In this paper, we propose an adaptive niching EDA based on Affinity Propagation (AP) clustering analysis. The AP clustering is used to adaptively partition the niches and mine the searching information from the evolution process. The obtained information is successfully utilized to improve the EDA performance by using a balance niching searching strategy. Two different categories of optimization problems are used to evaluate the proposed adaptive niching EDA. The first one is solving three benchmark functional multimodal optimization problems by a continuous EDA based on single Gaussian probabilistic model; the other one is solving a real complicated discrete EDA optimization problem, the HP model protein folding based on k-order Markov probabilistic model. Simulation results show that the proposed adaptive niching EDA is an efficient method.

In this paper, a joint blind synchronization and demodulation scheme is developed for ultra-wideband (UWB) impulse radio systems. Based on the prior knowledge of the direct-sequence (DS) spread codes, the proposed approach can achieve frame-level synchronization with the help of frame-rate samples. Taking advantage of the periodicity of the DS spread codes, the frame-level synchronization can be carried out even in one symbol interval. On the other hand, after timing acquisition, these frame-rate samples can be re-utilized also for demodulation. Thus the acquisition time and the implementation complexity are reduced considerably. The performance improvement can be justified by both theoretical analysis and simulation results, in terms of acquisition probability and bit error rate (BER).

In this letter, we analyze the average symbol error rate (SER) performance for multiple-input multiple-output (MIMO) wireless communication links with transmit beamforming and maximum ratio combining (MRC), known as MIMO-MRC, in the presence of multiple interferers in Rayleigh fading channels. An upper bound and an approximation of the average SER for M-ary signaling and an exact average SER for some modulation formats are evaluated. Moreover, an exact closed-form expression of the average SER in an interference-limited environment is derived. The analytical results are confirmed by numerical simulations.

The exact time complexity of Hsu and Huan's self-stabilizing maximal matching algorithm is provided. It is n2 + n - 2 if the number of nodes n is even and n2 + n - if n is odd.

Design of high gain and high efficiency antennas is one of the key challenges in antenna engineering and especially in millimeter wave communication systems. Various types of planar waveguide arrays with series-fed traveling wave operation have been developed in Tokyo Tech with the special focus upon efficiency enhancement as well as reduction of fabrication cost. In this review, four kinds of single layer waveguide arrays characterized with the series fed travelling wave operation are surveyed first. To cope with the bandwidth narrowing effects due to long line effects associated with the series fed operation, authors have introduced partially corporate feed embedded in the single layer waveguide. They further extended the study to cover fully corporate feed arrays with multiple layer waveguide as well; a new fabrication technique of diffusion bonding of laminated thin plates has the potential to realize the low cost mass production of multi-layer structures for the millimeter wave application. Secondly, the novel methods for loss evaluation of copper plate substrate are established for the design of post-wall waveguide arrays where dielectric loss and conductor loss is determined in wide range of millimeter wave band, by using the Whispering gallery mode resonator. This enables us to design the planar arrays with the loss taken into account. Finally, the planar arrays are now applied to two kinds of systems in the Tokyo Tech millimeter wave project; the indoor short range file-transfer systems and the outdoor communication systems for the medium range backhaul links. The latter has been field-tested in the model network built in Tokyo Tech Ookayama campus. Early stage progress of the project including unique propagation data is also reported.

Fuzzy cognitive maps (FCMs) are used to support decision-making, and the decision processes are performed by inference of FCMs. The inference greatly depends on activation functions such as sigmoid function, hyperbolic tangent function, step function, and threshold linear function. However, the sigmoid functions widely used for decision-making processes have been designed by experts. Therefore, we propose a method for designing sigmoid functions through Lyapunov stability analysis. We show the usefulness of the proposed method through the experimental results in inference of FCMs using the designed sigmoid functions.

In this paper a nonlinearity compensation algorithm based on the extended Kalman filter is proposed to improve the measurement accuracy of a heterodyne laser interferometer. The heterodyne laser interferometer is used for ultra-precision measurements such as those used in semiconductor manufacturing. However the periodical nonlinearity property caused by frequency-mixing restricts the accuracy of the nanometric measurements. In order to minimize the effect of the nonlinearity, the measurement process of the laser interferometer is modeled as a state equation and the extended Kalman filtering approach is applied to the process. The effectiveness of our proposed algorithm is demonstrated by comparing the results of the algorithm with experimental results for the laser system.

In this Letter, the maximum likelihood (ML) estimator for the parameters of a real sinusoid in additive white Gaussian noise using irregularly-spaced samples is derived. The ML frequency estimate is first determined by a one-dimensional search, from which optimum amplitude and phase estimates are then computed. It is shown that the estimation performance of the ML method can attain Cramér-Rao lower bound when the signal-to-noise ratio is sufficiently large.