A method for efficiently estimating the time-varying spectra of nonstationary autoregressive (AR) signals is derived using an indefinite matrix-based sliding window fast linear prediction (ISWFLP). In the linear prediction, the indefinite matrix plays a very important role in sliding an exponentially weighted finite-length window over the prediction error samples. The resulting ISWFLP algorithm successively estimates the time-varying AR parameters of order N at a computational complexity of O(N) per sample. The performance of the AR parameter estimation is superior to the performances of the conventional techniques, including the Yule-Walker, covariance, and Burg methods. Consequently, the ISWFLP-based AR spectral estimation method is able to rapidly track variations in the frequency components with a high resolution and at a low computational cost. The effectiveness of the proposed method is demonstrated by the spectral analysis results of a sinusoidal signal and a speech signal.

A compact 120-GHz-band finline orthomode transducer (OMT) with high isolation between orthogonal ports (Iop) was designed and fabricated for bidirectional wireless data transmission with polarization multiplexing. To achieve high Iop, finline OMTs normally use a resistive card to decrease unwanted resonance, that occurs on the finline, but adding a resistive card complicates the fabrication process and raises the cost of fabrication. Our proposed finline OMT uses an improved finline design in which the resonance frequency is controlled in order to expel unwanted resonance from the operation bandwidth of the 120-GHz-band wireless link. The proposed finline design enables high Iop without using a resistive card, which simplifies the fabrication process and lowers the cost of fabrication. A square horn antenna, which is attached to the finline OMT, is also designed to suppress unwanted polarization rotation of reflected waves, which further improves Iop. The proposed finline OMT has a transmission loss of less than 1.2dB, return loss of more than 12dB, cross polarization discrimination of more than 30dB, and Iop of more than 50dB across the entire occupied bandwidth of the 120-GHz-band wireless link. These characteristics are sufficient not only for 10-Gbit/s bidirectional data transmission but also for 20-Gbit/s unidirectional 2-ch data transmission by polarization-multiplexing.

This paper describes a very accurate method of estimating the return-path-capacitance and validates the estimation based on low-error measurements for electric-field intrabody communication. The return-path capacitance, Cg, of a mobile transceiver is estimated in two ways. One uses the attenuation factor in transmission and capacitance, Cb, between a human body and the earth ground. The other uses the attenuation factor in reception. To avoid the influence of the lead wire in the estimation of Cb, Cb is estimated from the attenuation factor measured with an amplifier with a low input capacitance. The attenuation factor in reception is derived by using the applied-voltage dependence of the reception rate. This way avoids the influence of any additional instruments on the return-path capacitance and allows that capacitance to be estimated under the same condition as actual intrabody communication. The estimates obtained by the two methods agree well with each other, which means that the estimation of Cb is valid. The results demonstrate the usefulness of the methods.

We calculated propagation constants of supermodes for two-dimensional two-slab waveguides, with small core gap, using second-order perturbation expansion from gapless slab waveguide system, and compared our results with the existing works. In the perturbation calculation, we used trapezoidal method to calculate the integral over the transverse direction in space and obtained second-order expansion of (core gap)/(core width) for propagation constants. Our result can explain the qualitative relationship between the propagation constants and the gap distance in the neighbor of (core gap)/(core width) being zero.

To help student nurses learn to transfer patients from a bed to a wheelchair, this paper proposes a system for automatic skill evaluation in nurses' training for this task. Multiple Kinect sensors were employed, in conjunction with colored markers attached to the trainee's and patient's clothing and to the wheelchair, in order to measure both participants' postures as they interacted closely during the transfer and to assess the correctness of the trainee's movements and use of equipment. The measurement method involved identifying body joints, and features of the wheelchair, via the colors of the attached markers and calculating their 3D positions by combining color and depth data from two sensors. We first developed an automatic segmentation method to convert a continuous recording of the patient transfer process into discrete steps, by extracting from the raw sensor data the defining features of the movements of both participants during each stage of the transfer. Next, a checklist of 20 evaluation items was defined in order to evaluate the trainee nurses' skills in performing the patient transfer. The items were divided into two types, and two corresponding methods were proposed for classifying trainee performance as correct or incorrect. One method was based on whether the participants' relevant body parts were positioned in a predefined spatial range that was considered ‘correct’ in terms of safety and efficacy (e.g., feet placed appropriately for balance). The second method was based on quantitative indexes and thresholds for parameters describing the participants' postures and movements, as determined by a Bayesian minimum-error method. A prototype system was constructed and experiments were performed to assess the proposed approach. The evaluation of nurses' patient transfer skills was performed successfully and automatically. The automatic evaluation results were compared with evaluation by human teachers and achieved an accuracy exceeding 80%.

This paper considers coordinated linear precoding for rate optimization in downlink multicell, multiuser orthogonal frequency-division multiple access networks. We focus on two different design criteria. In the first, the weighted sum-rate is maximized under transmit power constraints per base station. In the second, we minimize the total transmit power satisfying the signal-to-interference-plus-noise-ratio constraints of the subcarriers per cell. Both problems are solved using standard conic optimization packages. A less complex, fast, and provably convergent algorithm that maximizes the weighted sum-rate with per-cell transmit power constraints is formulated. We approximate the non-convex weighted sum-rate maximization (WSRM) problem with a solvable convex form by means of a sequential parametric convex approximation approach. The second-order cone formulations of an objective function and the constraints of the optimization problem are derived through a proper change of variables, first-order linear approximation, and hyperbolic constraints transformation. This algorithm converges to the suboptimal solution while taking fewer iterations in comparison to other known iterative WSRM algorithms. Numerical results are presented to demonstrate the effectiveness and superiority of the proposed algorithm.

KCipher-2 is a word-oriented stream cipher and an ISO/IEC 18033 standard. It is listed as a CRYPTREC cryptographic algorithm for Japanese governmental use. It consists of two feedback shift registers and a non-linear function. The size of each register in KCipher-2 is 32 bits and the non-linear function mainly applies 32-bit operations. Therefore, it can be efficiently implemented as software. SNOW-family stream ciphers are also word-oriented stream ciphers, and their high performance has already been demonstrated.We propose optimised implementations of KCipher-2 and compare their performance to that of the SNOW-family and other eSTREAM portfolios. The fastest algorithm is SNOW 2.0 and KCipher-2 is the second fastest despite the complicated irregular clocking mechanism. However, KCipher-2 is the fastest of the feasible algorithms, as SNOW 2.0 has been shown to have a security flaw. We also optimise the hardware implementation for the Virtex-5 field-programmable gate array (FPGA) and show two implementations. The first implementation is a rather straightforward optimisation and achieves 16,153 Mbps with 732 slices. In the second implementation, we duplicate the non-linear function using the structural advantage of KCipher-2 and we achieve 17,354 Mbps with 813 slices. Our implementation of KCipher-2 is around three times faster than those of the SNOW-family and efficiency, which is evaluated by “Throughput/Area (Mbps/slice)”, is 3.6-times better than that of SNOW 2.0 and 8.5-times better than that of SNOW 3G. These syntheses are performed using Xilinx ISE version 12.4.

In this letter, constructions of sequences with perfect odd autocorrelation and sequence sets with zero odd correlation zone (ZOCZ) over the 8-QAM+ constellation are presented. Based on odd perfect ternary sequences, odd perfect sequences and ZOCZ sequence sets over the 8-QAM+ constellation are constructed by using shift vectors and mappings. These odd perfect sequences and ZOCZ sequence sets over 8-QAM+ constellation can be used in communication systems to achieve high transmission data rate (TDR) and low interference.

This paper presents an application of the constained interpolation profile basis set (CIP-BS) method to electromagnetic fields analyses. Electromagnetic fields can be expanded in terms of multi-dimensional CIP basis functions, and the Galerkin method can then be applied to obtain a system of linear equations. In the present study, we focus on a two-dimensional problem with TMz polarization. In order to examine the precision of the CIP-BS method, TE202 resonant mode in a rectangular cavity is analyzed. The numerical results show that CIP-BS method has better performance than the finite-difference time-domain (FDTD) method when the time step is small. Then an absorbing boundary condition based on the perfectly matched layer (PML) is formulated, and the absorption performance is demonstrated. Finally, the propagation in an inhomogeneous medium is computed by using the proposed method, and it is observed that in the CIP-BS method, smooth variation of material constants is effectively formulated without additional computational costs, and that accurate results are obtained in comparison with the FDTD method even if the permittivity is high.

In signal restoration problems, we expect to improve the restoration performance with a priori information about unknown target signals. In this paper, the parametric Wiener filter with linear constraints for unknown target signals is discussed. Since the parametric Wiener filter is usually defined as the minimizer of the criterion not for the unknown target signal but for the filter, it is difficult to impose constraints for the unknown target signal in the criterion. To overcome this difficulty, we introduce a criterion for the parametric Wiener filter defined for the unknown target signal whose minimizer is equivalent to the solution obtained by the original formulation. On the basis of the newly obtained criterion, we derive a closed-form solution for the parametric Wiener filter with linear constraints.

A macroscopic structure was analyzed for a system comprising multiple elements in which the dynamics is affected by their distribution. First, a nonlinear Boltzmann equation, which has an integration term with respect to the distribution of the elements, was derived. Next, the moment vector equation (MVE) for the Boltzmann equation was derived. The average probability density function (pdf) in a steady state was derived using eigen analysis of the coefficient matrix of the MVE. The macroscopic structure of the system and the mechanism that provides the average pdf and the transient response were then analyzed using eigen analysis. Evaluation of the average pdf and transient response showed that using eigen analysis is effective for analyzing not only the transient and stationary properties of the system but also the macroscopic structure and the mechanism providing the properties.

The results of fishery investigations are used to estimate the catch size, times fish are caught, and future stock in the fish culture industry. In Tokoro, Japan, scallop farms are located on gravel and sand seabed. Seabed images are necessary to visually estimate the number of scallops of a particular farm. However, there is no automatic technology for measuring resources quantities and so the current investigation technique is the manual measurement by experts. We propose a method to extract scallop areas from images of sand seabed. In the sand field, we can see only the shelly rim because the scallop is covered with sand and opens and closes its shell while it is alive and breathing. We propose a method to extract the shelly rim areas under varying illumination, extract the scallop areas using the shelly rims based on professional knowledge of the sand field, explain the results, and evaluate the method's effectiveness.

We implemented a scalar multiplication method over elliptic curves using division polynomials. We adapt an algorithm for computing elliptic nets proposed by Stange. According to our experimental results, the scalar multiplication method using division polynomials is faster than the binary method in an affine coordinate system.

Coupled with the discrete wavelet transform, SPIHT (set partitioning in hierarchical trees) is a highly efficient image compression technique that allows for progressive transmission. One problem, however, is that its decoding can be extremely sensitive to bit errors in the code sequence. In this paper, we address the issue of transmitting SPIHT-encoded images via noisy channels, wherein errors are inevitable. The communication scenario assumed in this paper is that the transmitter cannot get any acknowledgement from the receiver. In our scheme, the original SPIHT code sequence is first segmented into packets. Each packet is classified as either a CP (critical packet) or an RP (refinement packet). For error control, cyclic redundancy check (CRC) is incorporated into each packet. By checking the CRC check sum, the receiver is able to tell whether a packet is correctly received or not. In this way, the noisy channel can be effectively modeled as an erasure channel. For unequal error protection (UEP), each of those packets are repeatedly transmitted for a few times, as determined by a process called diversity allocation (DA). Two DA algorithms are proposed. The first algorithm produces a nearly optimal decoded image (as measured in the expected signal-to-noise ratio). However, its computation cost is extremely high. The second algorithm works in a progressive fashion and is naturally compatible with progressive transmission. Its computation complexity is extremely low. Nonetheless, its decoded image is nearly as good. Experimental results show that the proposed scheme significantly improves the decoded images. They also show that making distinction between CP and RP results in wiser diversity allocation to packets and thus produces higher quality in the decoded images.

In this paper, the authors present a CAM-based Information Detection Hardware System for fast, exact and approximate image matching on 2-D data, using FPGA. The proposed system can be potentially applied to fast image matching with various required search patterns, without using search principles. In designing the system, we take advantage of Content Addressable Memory (CAM) which has parallel multi-match mode capability and has been designed, using dual-port RAM blocks. The system has a simple structure, and does not employ any Central Processor Unit (CPU) or complicated computations.

Two classes of 3rd order correlation immune symmetric Boolean functions have been constructed respectively in [1] and [2], in which some interesting phenomena of the algebraic degree have been observed as well. However, a good explanation has not been given. In this paper, we obtain the formulas for the degree of these functions, which can well explain the behavior of their degree.

This paper investigates the average block error rate (BLER) performance of star 16QAM schemes considering the effective peak-to-average power ratio (PAPR) criterion called a cubic metric (CM) for uplink discrete Fourier transform (DFT)-precoded orthogonal frequency division multiple access (OFDMA). We clarify the best ring amplitude ratio for the (4, 12) and (8, 8) star 16QAM schemes from the viewpoint of the required average signal-to-noise power ratio (SNR) that satisfy the target average BLER based on link-level simulations. We also validate the agreement of the best ring amplitude ratios with those maximizing the mutual information based throughput. Then, employing the best ring amplitude ratios for the respective coding rates of the turbo code, we show that (8, 8) star 16QAM achieves better average BLER performance compared to that for (4, 12) star 16QAM. Moreover, we show the effectiveness of the (8, 8) star 16QAM scheme compared to square 16QAM in terms of the required average received SNR considering the CM when the coding rate is low such as 1/3 for uplink DFT-precoded OFDMA.

This paper deals with carrier frequency offset (CFO) estimation based on the minimum variance distortionless response (MVDR) criterion without using specific training sequences for interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. In the presence of large CFOs, the estimator is proposed to find a new CFO vector based on the first-order Taylor series expansion of the one initially given. The problem of finding the new CFO vector is formulated as the closed form of a generalized eigenvalue problem, which allows one to readily solve it. Since raising the accuracy of residual CFO estimation can provide more accurate residual CFO compensation, this paper also present a decision-directed MVDR approach to improve the CFO estimation performance. However, the proposed estimator can estimate CFOs with less computation load. Several computer simulation results are provided for illustrating the effectiveness of the proposed blind estimate approach.

In multi-static sonar systems, the least square (LS) and maximum likelihood (ML) are the typical estimation criteria for target location estimation. The LS localizaiton has the advantage of low computational complexity. On the other hand, the performance of LS can be degraded severely when the target lies on or around the straight line between the source and receiver. We examine mathematically the reason for the performance degradation of LS. Then, we propose a location adaptive — least square (LA-LS) localization that removes the weakness of the LS localizaiton. LA-LS decides the receivers that produce abnormally large measurement errors with a proposed probabilistic measure. LA-LS achieves improved performance of the LS localization by ignoring the information from the selected receivers.

We describe a novel idea to improve machine translation by combining multiple candidate translations and extra translations. Without manual work, extra translations can be generated by identifying and hybridizing the syntactic equivalents in candidate translations. Candidate and extra translations are then combined on sentence level for better general translation performance.