With the emergence of a large quantity of data in science and industry, it is urgent to improve the prediction accuracy and reduce the high complexity of Gaussian process regression (GPR). However, the traditional global approximation and local approximation have corresponding shortcomings, such as global approximation tends to ignore local features, and local approximation has the problem of over-fitting. In order to solve these problems, a large-scale Gaussian process regression algorithm (RFFLT) combining random Fourier features (RFF) and local approximation is proposed. 1) In order to speed up the training time, we use the random Fourier feature map input data mapped to the random low-dimensional feature space for processing. The main innovation of the algorithm is to design features by using existing fast linear processing methods, so that the inner product of the transformed data is approximately equal to the inner product in the feature space of the shift invariant kernel specified by the user. 2) The generalized robust Bayesian committee machine (GRBCM) based on Tsallis mutual information method is used in local approximation, which enhances the flexibility of the model and generates a sparse representation of the expert weight distribution compared with previous work. The algorithm RFFLT was tested on six real data sets, which greatly shortened the time of regression prediction and improved the prediction accuracy.

This paper reports the development of a landmine visualization system based on complex-valued self-organizing map (CSOM) by employing one-dimensional (1-D) array of taper-walled tapered slot antennas (TSAs). Previously we constructed a high-density two-dimensional array system to observe and classify complex-amplitude texture of scattered wave. The system has superiority in its adaptive distinction ability between landmines and other clutters. However, it used so many (144) antenna elements with many mechanical radio-frequency (RF) switches and cables that it has difficulty in its maintenance and also requires long measurement time. The 1-D array system proposed here uses only 12 antennas and adopts electronic RF switches, resulting in easy maintenance and 1/4 measurement time. Though we observe stripe noise specific to this 1-D system, we succeed in visualization with effective solutions.

During a software development phase where a product is progressively elaborated, it is difficult to guarantee that the refined product retains its original behaviors. In this paper, we propose a method to detect refinement errors in UML sequence diagrams using LTSA (Labeled Transition System Analyzer). The method integrates multiple sequence diagrams using hMSC (high-level Message Sequence Charts) into a sequence diagram. Then, the method translates the diagram into FSP representation, which is the input language of LTSA. The method also supports some combined fragment operators in the UML 2.0 specification. We applied the method to some examples of refined sequence diagrams and checked the correctness of refinement. As a result, we confirmed the method can detect refinement errors in practical time.

In this paper, we introduce a generalized minimum mean-square error short-time spectral amplitude estimator with a new prior estimation of the speech probability density function based on moment-cumulant transformation. From the objective and subjective evaluation experiments, we show the improved noise reduction performance of the proposed method.

Antipodal Fermi antenna (APFA) that uses an antipodal feeding section is proposed and its fundamental characteristics are presented. It is shown that the cross polarization level is decreased by 5–10 dB by the presence of the corrugation. It is also found that high gain, low VSWR and low side lobes and low back lobes are obtained. The mechanism of operation principles is discussed by using FDTD analysis. It is found that the corrugation transforms the current of parallel line mode to the current of traveling wave radiation mode and the effective aperture is enlarged which yields high gain characteristics.

A new linearly tapered slot antenna (LTSA) with defected sides is proposed in this letter. Both sides are defected with half-dumbbell shape slots that may alter the surface current intensities on both sides. As the half-dumbbell size is increased, the 3-dB beamwidth of the proposed antenna is 4° and 6° lower in the E/H-plane, respectively, than these of the LTSA without defects. Accordingly, the measured gain is improved by up to 3.75 dB and the first side lobe level is lowered by about -10.8 dB and -5.8 dB in the E/H-planes, respectively.

We propose a method for camera calibration based on image registration. This method registers two images; one is a real image captured by a camera with a calibration object with known shape and texture, and the other is a synthetic image containing the object. The proposed method estimates the parameters of the rotation and translation of the object by using the depth information of the synthetic image. The Gauss-Newton method is used to minimize the residuals of intensities of the two images. The proposed method does not depend on initial values of the minimization, and is applicable to images with much noise. Experimental results using real images demonstrate the robustness against initial state and noise on the image.