This paper presents a mathematically simple method of maximum SINR (Signal to Interference plus Noise Ratio) design of broadband MIMO (Multiple Input Multiple Output) communication systems adopting TDL (Tapped Delay Line) structure for spatio-temporal processing in both transmitter and receiver sides. The weight vectors in both ends are determined alternately, optimizing one side by fixing the other, and this operation is repeated until the SINR converges. The performance of MIMO systems using the proposed approach is investigated through computer simulations, and it is demonstrated that, though it requires high computational cost, the TDL structure brings high ability to mitigate the influence of frequency selective fading, particularly when the duration of the delay profile is long. Moreover, experimental results show that the equable distribution of the resources (weights and delay units) to both arrays is better choice than the concentration of them to one side of the transmitter or receiver.

From lessons learned in medical data mining projects we show that integration of advanced computation techniques and human inspection is indispensable in medical data mining. We proposed an integrated approach that merges data mining and text mining methods plus visualization support for expert evaluation. We also appropriately developed temporal abstraction and text mining methods to exploit the collected data. Furthermore, our visual discovery system D2MS allowed to actively and effectively working with physicians. Significant findings in hepatitis study were obtained by the integrated approach.

The compound element pseudo-transient analysis (PTA) algorithm is an effective practical method for finding the DC operating point when the Newton-Raphson method fails. It is able to effectively prevent from the oscillation problems compared with conventional PTA algorithms. In this paper, an effective SPICE3 implementation method for the compound element PTA algorithm is proposed. It has the characteristic of not expanding the Jacobian matrix and not changing the Jacobian matrix structure when the pseudo-transient numerical simulation is being done. Thus a high simulation efficiency is guaranteed. The ability of the proposed SPICE3 implementation to avoid the oscillation problems and the simulation efficiency are demonstrated by examples.

In this paper, we present a novel force-directed method for automatically drawing intersecting compound mixed graphs (ICMGs) that can express complicated relations among elements such as adjacency, inclusion, and intersection. For this purpose, we take a strategy called unified simplification that can transform layout problem for an ICMG into that for an undirected graph. This method is useful for various information visualizations. We describe definitions, aesthetics, force model, algorithm, evaluation, and applications.

This paper examines seasonal change of the true water area of Lake "Sakata" by using Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. The true water area includes not only the body of water but also the water area under emerged-plants and/or floating-leave plants in the lake. Statistical POLSAR image analysis is carried out for both X- and L-band data, based on the three-component scattering power decomposition method, where the decomposed components are surface scattering, double-bounce scattering and volume scattering components. From the results of the image analysis for the L-band POLSAR data acquired by Pi-SAR system, it is found that strong double-bounce scattering can be observed at the vicinity of the boundary region between water area and the surrounding emerged-plants area in early and middle summer. This phenomenon is an important factor for environmental monitoring. To verify the generating mechanism of the double-bounce scattering, the Finite-Difference Time-Domain (FDTD) polarimetric scattering analysis is also executed for a simplified boundary model, which simulates the local boundary region around the lake and consists of lots of vertical thin dielectric pillars on a perfect electric conductor (PEC) plate or on a PEC and dielectric hybrid plate. Taking into account the polarimetric feature of the double-bounce scattering obtained by both the FDTD and POLSAR image analyses, one can distinguish the actual water area from the bush of the emerged-plants around the lake, even when the water area is concealed by emerged-plants and/or floating-leave plants. Consequently, it is found that by using the proposed approach, one can estimate the true water area seasonal change for the lake and the surrounding wetland.

Due to the continuous growth of wireless communication technology and mobile equipment, the history management of moving object is important in a wide range of location-based applications. To process queries for history data, trajectories, we generally use trajectory-preserving index schemes based on the trajectory preservation property. This property means that a leaf node only contains segments belonging to a particular trajectory, regardless of the spatiotemporal locality of segments. The sacrifice of spatiotemporal locality, however, causes the index to increase the dead space of MBBs of non-leaf nodes and the overlap between the MBBs of nodes. Therefore, an index scheme for trajectories shows good performance with trajectory-based queries, but not with coordinate-based queries, such as range queries. We propose new index schemes that improve the performance of range queries without reducing performance with trajectory based queries.

In multiple-input multiple-output (MIMO) wireless relay networks, simultaneously using multiple relay nodes can improve the capacity of source-to-destination communications. Recent information theories have shown that passing the same message across multiple relay nodes can improve the capacity of source-to-destination communications. We have previously proposed three relay schemes that use jointly QR decomposition and the phase control matrix; computer simulations have confirmed the superiority of these schemes over conventional ones such as amplify-and-forward and zero-forcing schemes. In this paper, we analyze the capacity and achievable gains (distributed array gain, intra-node array gain and spatial multiplexing gain) of the previously proposed relay schemes (QR-P-QR, QR-P-ZF, and ZF-P-QR) and thus provide an insight into what contributes to their superiority over conventional schemes. The analyses show that the location of the relay nodes used has a significant impact on capacity. On the basis of this observation, we further propose a method that enables each relay node to individually select its relay scheme according to its channel conditions so as to maximize the capacity. A computer simulation confirms the capacity improvement achieved by the proposed selection method.

This paper proposes a new adaptive filter algorithm for system identification by using an independent component analysis (ICA) technique, which separates the signal from noisy observation under the assumption that the signal and noise are independent. We first introduce an augmented state-space expression of the observed signal, representing the problem in terms of ICA. By using a nonparametric Parzen window density estimator and the stochastic information gradient, we derive an adaptive algorithm to separate the noise from the signal. The proposed ICA-based algorithm does not suppress the noise in the least mean square sense but to maximize the independence between the signal part and the noise. The computational complexity of the proposed algorithm is compared with that of the standard NLMS algorithm. The stationary point of the proposed algorithm is analyzed by using an averaging method. We can directly use the new ICA-based algorithm in an acoustic echo canceller without double-talk detector. Some simulation results are carried out to show the superiority of our ICA method to the conventional NLMS algorithm.

This paper deals with adaptive array beamforming based on stochastic gradient descent independent component analysis (ICA) for suppressing interference with robust capabilities. The approach first uses estimates of the interested source directions to construct the multiple regularized constraints, which form an efficient ICA-based beamformer to achieve fast convergence and more robust capabilities than existing MCMV and ESB beamformers. In conjunction with the regularization parameters of the high-order derivative constraints, the width of the main beam for remaining the desired signal and the depth of nulls for suppressing interferers can be adjusted. Several computer simulation examples are provided for illustration and comparison.

This paper presents a novel feature extraction algorithm based on particle swarms for processing hyperspectral imagery data. Particle swarm optimization, originally developed for global optimization over continuous spaces, is extended to deal with the problem of feature extraction. A formulation utilizing two swarms of particles was developed to optimize simultaneously a desired performance criterion and the number of selected features. Candidate feature sets were evaluated on a regression problem. Artificial neural networks were trained to construct linear and nonlinear models of chemical concentration of glucose in soybean crops. Experimental results utilizing real-world hyperspectral datasets demonstrate the viability of the method. The particle swarms-based approach presented superior performance in comparison with conventional feature extraction methods, on both linear and nonlinear models.

This paper investigates the use of the affine transformation matrix when employing principal component analysis (PCA) to compress the data of 3D animation models. Satisfactory results were achieved for the common 3D models by using PCA because it can simplify several related variables to a few independent main factors, in addition to making the animation identical to the original by using linear combinations. The selection of the principal component factor (also known as the base) is still a subject for further research. Selecting a large number of bases could improve the precision of the animation and reduce distortion for a large data volume. Hence, a formula is required for base selection. This study develops an automatic PCA selection method, which includes the selection of suitable bases and a PCA separately on the three axes to select the number of suitable bases for each axis. PCA is more suitable for animation models for apparent stationary movement. If the original animation model is integrated with transformation movements such as translation, rotation, and scaling (RTS), the resulting animation model will have a greater distortion in the case of the same base vector with regard to apparent stationary movement. This paper is the first to extract the model movement characteristics using the affine transformation matrix and then to compress 3D animation using PCA. The affine transformation matrix can record the changes in the geometric transformation by using 44 matrices. The transformed model can eliminate the influences of geometric transformations with the animation model normalized to a limited space. Subsequently, by using PCA, the most suitable base vector (variance) can be selected more precisely.

The possibility of using three kinds of new type composite materials as material for high speed sliding contacts was investigated. The results of this investigation were compared with the results of the low speed tests that were reported earlier. As a result of the above, it was discovered that for high speed rotation in the range from 0.014 m/s to 2 m/s, the order of merit did not significantly change. Based on this, it was concluded that if solid lubricant is effectively supplied to the sliding surface, the influence by frictional heat generated by high speed is slight. Of the three kinds of composite material, it was clarified that composite material (CMML-1) had the lowest contact resistance and Composite Material (CMML-3) had the lowest maximum frictional coefficient of friction. 'CM' and 'ML' are initialisms for 'Composite Material' and 'Material of Lubrication' respectively. The number that is attached to the material name is a numeric value that was set by this laboratory.

Internet access traffic follows hourly patterns that depend on various factors, such as the periods users stay on-line at the access point (e.g. at home or in the office) or their preferences for applications. The clustering of Internet users may provide important information for traffic engineering and billing. For example, it can be used to set up service differentiation according to hourly behavior, resource optimization based on multi-hour routing and definition of tariffs that promote Internet access in low busy hours. In this work, we propose a methodology for clustering Internet users with similar patterns of Internet utilization, according to their hourly traffic utilization. The methodology resorts to three statistical multivariate analysis techniques: cluster analysis, principal component analysis and discriminant analysis. The methodology is illustrated through measured data from two distinct ISPs, one using a CATV access network and the other an ADSL one, offering distinct traffic contracts. Principal component analysis is used as an exploratory tool. Cluster analysis is used to identify the relevant Internet usage profiles, with the partitioning around medoids and Ward's method being the preferred clustering methods. For the two data sets, these methods lead to the choice of 3 clusters with different hourly traffic utilization profiles. The cluster structure is validated through discriminant analysis. It is also evaluated in terms of several characteristics of the user traffic not used in the cluster analysis, such as the type of applications, the amount of downloaded traffic, the activity duration and the transfer rate, resulting in coherent outcomes.

The design of the finite impulse response (FIR) notch filter with controlled null width is expressed as a derivatively contrained quadratic optimization problem. The problem is transformed into an unconstrained one by choosing a null matrix orthogonal to the derivative constraint matrix. In this paper, subband decomposition using wavelet filters is employed to construct the null matrix. Taking advantage of the vanishing moment property of the wavelet filters, the proposed method can adjust the null width of the notch filter for eliminating the intractable iterference by controlling the regularity of the wavelet filters. Simulation results show that the new method can offer comparable performance as those of the existing full-rank-based ones and thus provides a promising alternative to the existing works.

In order to improve the antenna gain, a composite right/left-handed (CRLH) leaky-wave (LW) antenna composed of symmetrical unit cells with short stubs terminated by vertical vias is designed. The use of symmetrical unit cells suppresses the cross-polarization of radiation to less than 23 dB. By comparing the measured radiation characteristics to that of a conventional CRLH LW antenna without short stub in the X-band, it is shown that the presented CRLH LW antenna with 51 unit cells offers a narrower beam and the antenna gain improves 4.1, 2.2 and 3.1 dB in the backward, broadside and forward directions of radiation, respectively.

In this paper, a novel independent component analysis (ICA) approach is proposed, which is robust against the interference of impulse noise. To implement ICA in a noisy environment is a difficult problem, in which traditional ICA may lead to poor results. We propose a method that consists of noise detection and image signal recovery. The proposed approach includes two procedures. In the first procedure, we introduce a self-organizing map (SOM) network to determine if the observed image pixels are corrupted by noise. We will mark each pixel to distinguish normal and corrupted ones. In the second procedure, we use one of two traditional ICA algorithms (fixed-point algorithm and Gaussian moments-based fixed-point algorithm) to separate the images. The fixed-point algorithm is proposed for general ICA model in which there is no noise interference. The Gaussian moments-based fixed-point algorithm is robust to noise interference. Therefore, according to the mark of image pixel, we choose the fixed-point or the Gaussian moments-based fixed-point algorithm to update the separation matrix. The proposed approach has the capacity not only to recover the mixed images, but also to reduce noise from observed images. The simulation results and analysis show that the proposed approach is suitable for practical unsupervised separation problem.

In arithmetic circuits for digital signal processing, radixes other than two are often used to make circuits faster. In such cases, radix converters are necessary. However, in general, radix converters tend to be complex. This paper considers design methods for p-nary to binary converters. First, it considers Look-Up Table (LUT) cascade realizations. Then, it introduces a new design technique called arithmetic decomposition by using LUTs and adders. Finally, it compares the amount of hardware and performance of radix converters implemented by FPGAs. 12-digit ternary to binary converters on Cyclone II FPGAs designed by the proposed method are faster than ones by conventional methods.

This paper presents a method for blind identification of a system whose transfer matrix is non-invertible at infinity, based on independent component analysis. In the proposed scheme, the transfer matrix to be identified is pre-multiplied by an appropriate polynomial matrix, named interactor, in order to compensate the row relative degrees and obtain a biproper system. It is then pre-multiplied by a demixing matrix via an existing approximate method. Both of these matrices are estimated blindly, i.e. with the input signals being unknown. The identified system is thus obtained as the inverse of the multiplication of these matrices.

A method for searching minimum Euclidean distances of respective substreams for different modulation orders of M-ary quadrature amplitude modulation signals in multiple-input and multiple-output systems is described. A channel matrix is cyclically-sorted sequentially and QR-decomposed. Using upper triangular matrices obtained by QR decomposition, minimum Euclidean distances are searched over trellis diagrams consisting of symbol-difference lattice points by computationally efficient multiple trellis-search algorithms. The simulation results demonstrate that per-substream minimum Euclidean distances can be detected with a high correct-estimation probability by path-re-searching controls over different modulation orders.

Recently, the superimposed pilot channel estimation has attracted attention for wireless communications, where the pilot symbol sequence is superimposed on a data symbol sequence and transmitted together, and thus there is no drop in information rate. In the superimposed pilot channel estimation, the receiver correlates the received symbol sequence with the pilot symbol sequence, and obtains the channel estimate. However, the correlation between the pilot symbol sequence and the data symbol sequence deteriorates the channel estimation accuracy. In particular, the channel estimation accuracy of the superimposed pilot channel estimation scheme is significantly deteriorated in MIMO systems, because the pilot symbol power of each transmit antenna to the total transmit power of all transmit antennas becomes smaller as the number of transmit antennas increases. On the other hand, it has been well known that the SAGE algorithm is an effective method for channel estimation and data detection. This algorithm is particularly effective in MIMO systems, because the operation of this algorithm can cancel the interference from other transmit antennas. In this paper, we evaluate the performance of the SAGE algorithm for channel estimation and data detection using superimposed pilot channel estimation in MIMO systems. From the results of computer simulations, we show that the system using the SAGE algorithm with superimposed training can achieve the good BER performances by using the SAGE algorithm with iteration.