A fast cross-validation algorithm for model selection in kernel ridge regression problems is proposed, which is aiming to further reduce the computational cost of the algorithm proposed by An et al. by eigenvalue decomposition of a Gram matrix.

In this paper, a compact controlled reception pattern antenna (CRPA) array based on a mu-zero resonance (MZR) antenna is proposed for a global positioning system (GPS). The MZR antenna can be minimized by designing structure based in mu-negative (MNG) transmission line. The MNG transmission line can be implemented by a gap structure for the series capacitance and a shorting via for a short-ended boundary condition. The CRPA array, which operates in L1 (1.57542GHz) and L2 (1.2276GHz) bands, is designed as a cylinder with a diameter and a height of 127mm (5 inches) and 20mm, respectively, and is composed of seven radiating elements. To design the compact CRPA array with high performance attributes such as an impedance matching (VSWR) value of less than 2, an isolation between array elements (<-12dB), an axial ratio (<5dB), and a circular polarization (CP) gain (>-1dBic: L1 band and >-3dBic: L2 band), we employ two orthogonal MZR antennas, a superstrate, and chip couplers. The performances of the CRPA antenna are verified and compared by an analytic analysis, a full-wave simulation, and measurements.

The goal of dimension reduction is to represent high-dimensional data in a lower-dimensional subspace, while intrinsic properties of the original data are kept as much as possible. An important challenge in unsupervised dimension reduction is the choice of tuning parameters, because no supervised information is available and thus parameter selection tends to be subjective and heuristic. In this paper, we propose an information-theoretic approach to unsupervised dimension reduction that allows objective tuning parameter selection. We employ quadratic mutual information (QMI) as our information measure, which is known to be less sensitive to outliers than ordinary mutual information, and QMI is estimated analytically by a least-squares method in a computationally efficient way. Then, we provide an eigenvector-based efficient implementation for performing unsupervised dimension reduction based on the QMI estimator. The usefulness of the proposed method is demonstrated through experiments.

This paper proposes the design of small CRPA arrays for dual-band Global Positioning System (GPS) applications. The array consists of five elements and is mounted on a circular ground platform with a diameter of 15-cm. Each antenna element has a coupled feed structure and consists of a feed patch and two radiating patches for dual-band operation. An external chip coupler is utilized for a broad circular polarization (CP) bandwidth, and its measured characteristics are taken into account in our simulation for more accurate performance estimation. Detailed parameters are optimized by using a genetic algorithm (GA) in conjunction with the FEKO EM simulator. The optimized antenna is fabricated on a ceramic substrate, and its performance is measured in a full anechoic chamber. Furthermore, a field test is also conducted to verify the signal-to-noise ratio (SNR) for real GPS satellite signals. The results prove that the proposed array is suitable for use in GPS CRPA applications.

Image restoration based on Bayesian estimation in most previous studies has assumed that the noise accumulated in an image was independent for each pixel. However, when we take optical effects into account, it is reasonable to expect spatial correlation in the superimposed noise. In this paper, we discuss the restoration of images distorted by noise which is spatially correlated with translational symmetry in the realm of probabilistic processing. First, we assume that the original image can be produced by a Gaussian model based on only a nearest-neighbor effect and that the noise superimposed at each pixel is produced by a Gaussian model having spatial correlation characterized by translational symmetry. With this model, we can use Fourier transformation to calculate system characteristics such as the restoration error and also minimize the restoration error when the hyperparameters of the probabilistic model used in the restoration process coincides with those used in the formation process. We also discuss the characteristics of image restoration distorted by spatially correlated noise using a natural image. In addition, we estimate the hyperparameters using the maximum marginal likelihood and restore an image distorted by spatially correlated noise to evaluate this method of image restoration.

In the execution on a smart card, elliptic curve cryptosystems have to be secure against side channel attacks such as the simple power analysis (SPA), the differential power analysis (DPA), and the refined power analysis (RPA), and so on. MMM-algorithm proposed by Mamiya, Miyaji, and Morimoto is a scalar multiplication algorithm secure against SPA, DPA, and RPA, which can decrease the computational complexity by increasing the size of a pre-computed table. However, it provides only 4 different cases of pre-computed tables. From the practical point of view, a wider range of time-memory tradeoffs is usually desired. This paper generalizes MMM-algorithm to improve the flexibility of tables as well as the computational complexity. Our improved algorithm is secure, efficient and flexible for the storage size.

In the execution on a smart card, side channel attacks such as the simple power analysis (SPA) and the differential power analysis (DPA) have become serious threat. Side channel attacks monitor the side channel information such as power consumption and even exploit the leakage information related to power consumption to reveal bits of a secret key d although d is hidden inside a smart card. Almost public key cryptosystems including RSA, DLP-based cryptosystems, and elliptic curve cryptosystems execute an exponentiation algorithm with a secret-key exponent, and they thus suffer from both SPA and DPA. In the case of elliptic curve cryptosystems, DPA is improved to the refined power analysis (RPA), which exploits a special point with a zero value and reveals a secret key. RPA is further generalized to zero-value register attack (ZRA). Both RPA and ZRA utilize a special feature of elliptic curves that happens to have a special point or a register used in addition and doubling formulae with a zero value and that the power consumption of 0 is distinguishable from that of a non-zero element. To make the matters worse, some previous efficient countermeasures to DPA are neither resistant to RPA nor ZRA. This paper focuses on elegant countermeasures of elliptic curve exponentiations against RPA, ZRA, DPA and SPA. Our novel countermeasure is easily generalized to be more efficient algorithm with a pre-computed table.

This paper presents an efficient VLSI architecture of biorthogonal (9,7)/(5,3) lifting based discrete wavelet transform that is used by lossy or lossless compression of JPEG2000. To improve hardware utilization of RPA (Recursive Pyramid Algorithm) implementation, we make the filter that is responsible for row operations of the first level perform both column operations and row operations of the second and following levels. As a result, the architecture has 66.7-88.9% hardware utilization. It requires 9 multipliers, 12 adders, and 12N line memories for NN image, which is smaller hardware complexity compared to that of other architectures with comparable throughput.

While superpages are an efficient solution to increase TLB reach, strong contraint for using superpages hinders the actual utilization. Two previous solutions, a partial-subblock TLB and the shadow memory were proposed to loose the contraint. A partial-subblock TLB looses only a small portion of the contraint and limits the superpage size at a cost. The shadow memory looses most of the constraint but introduces other serious problems. We propose three novel approaches to improve superpage supports. First, we propose a hybrid scheme which integrates both the shadow memory and a partial-subblock TLB, thereby enjoying the benefits inherited from both sides. The hybrid scheme has as high a superpage utilization as the shadow memory, and avoids most of the problems in the shadow memory by the virtue of partial-subblock TLB. Second, VS-TLBs are an extension of subblock TLBs to support multiple page subblocks, while subblock TLBs can support only single page subblocks. VS-TLBs have a much larger TLB reach than subblock TLBs with a cost of a small number of bits. Last, we propose VS-hybrid which replaces the partial-subblock TLB in the hybrid scheme with a partial VS-TLB. It supports multiple page subblocks in the hybrid scheme. Therefore, it takes both advantages of the hybrid scheme and the expanded subblock size. The simulation results show that the proposed schemes take a large amount of performance gain in the benchmark application programs.