Analytical expressions based on the Gauss-Chebyshev quadrature (GCQ) rule technique are derived to evaluate the bit-error rate (BER) for the time-hopping pulse position modulation (TH-PPM) ultra-wide band (UWB) systems under a Nakagami-m fading channel. The analyses are validated by the simulation results and adopted to assess the accuracy of the commonly used Gaussian approximation (GA) method. The influence of the fading severity on the BER performance of TH-PPM UWB system is investigated.

Hwang-Lo-Lin proposed a user identification scheme [3] based on the Maurer-Yacobi scheme [6] that is suitable for application to the mobile environment. Hwang-Lo-Lin argued that their scheme is secure against any attack. Against the Hwang-Lo-Lin argument, Liu-Horng-Liu showed that the Hwang-Lo-Lin scheme is insecure against a Liu-Horng-Liu attack mounted by an eavesdrop attacker. However, Liu-Horng-Liu did not propose any improved version of the original identification scheme which is still secure against the Liu-Horng-Liu attack. In this paper, we propose an identification scheme that can solve this problem and a non-interactive public key distribution scheme also.

This letter mainly focuses on improving current noise reduction methods to solve the critical speech distortion problems with robust noise reduction in noisy speech signals for speech enhancement over IP networks. For robust noise reduction with packet loss recovery, we propose a novel optimized Wiener filtering technique that uses the estimated SNR (Signal-to-Noise Ratio) with packet loss recovery method which is applied as post-filtering over IP-networks. Simulation results demonstrate that the proposed scheme provides better reduction and recovery rates with considering packet loss and SNR environment than other methods.

Recently, multi-carrier code division multiple access (MC-CDMA) has been attracting much attention as a broadband wireless access technique for the next generation mobile communication systems. Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can take advantage of the channel frequency-selectivity and improve the average bit error rate (BER) performance due to frequency-diversity gain. The conventional FDE requires the insertion of the guard interval (GI) to avoid the inter-block interference (IBI), resulting in the transmission efficiency loss. In this paper, an overlap FDE technique, which requires no GI insertion, is presented for MC-CDMA transmission. An expression for the conditional BER is derived for the given set of channel gains. The average BER performance in a frequency-selective Rayleigh fading channel is evaluated by Monte-Carlo numerical computation method using the derived conditional BER and is confirmed by computer simulation of the signal transmission.

Superconductivity and superconducting electronics have quite a prominent place in the European research environment and can look back onto a successful history. In recent years the European Framework programs helped to enhance the interaction between the different national research institutions, universities and industry. For applications of superconductivity this was accomplished by the European Network of Excellence SCENET and its sister organization ESAS. In this context a virtual European foundry network was established (Fluxonics), which forms a platform for the superconducting electronics activities in Europe and realizes support for the design and the fabrication of superconducting circuits for research laboratories and industry. Lately quite some development on the digital side and the cooling of superconducting electronics devices has taken place in Europe; most of it within the Fluxonics network. Some of these advances will be reported in this overview article.

We present a low-complexity maximum likelihood (ML) detector for a coded double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) system. The proposed ML detector exploits properties of two permuted equivalent channel matrices and multiple decision-feedback (DF) detections. This can reduce computational efforts from O(|A|4) to O(2|A|2) with maintaining ML performance, where |A| is the modulation order. Numerical results shows that the proposed ML detector obtains ML performance and requires remarkably lower computational loads compared with the conventional ML detector.

To precisely model the time dependency of features is one of the important issues for speech recognition. Segmental unit input HMM with a dimensionality reduction method has been widely used to address this issue. Linear discriminant analysis (LDA) and heteroscedastic extensions, e.g., heteroscedastic linear discriminant analysis (HLDA) or heteroscedastic discriminant analysis (HDA), are popular approaches to reduce dimensionality. However, it is difficult to find one particular criterion suitable for any kind of data set in carrying out dimensionality reduction while preserving discriminative information. In this paper, we propose a new framework which we call power linear discriminant analysis (PLDA). PLDA can be used to describe various criteria including LDA, HLDA, and HDA with one control parameter. In addition, we provide an efficient selection method using a control parameter without training HMMs nor testing recognition performance on a development data set. Experimental results show that the PLDA is more effective than conventional methods for various data sets.

A novel dual mode bandpass filter (BPF) with improved spurious response is presented in this letter. To obtain low insertion loss, the coupling structure using the dual mode resonator and the feeding scheme using coplanar-waveguide (CPW) are constructed on the two sides of a dielectric substrate. A defected ground structure (DGS) is designed on the ground plane of the CPW to achieve the goal of spurious suppression of the filter. The filter has been investigated numerically and experimentally. Measured results show a good agreement with the simulated analysis.

This paper is aimed to present the design and feasibility investigations of adopting the available on-site optical inspection system, which is commonly used for steel plate dimension measurement, to supply on-line dynamic gap measurements of a non-contacting conveyance structure in a steel mill. Adequate software and hardware implementations based on digital image processing techniques have been adapted to the entire system formulations and estimations. Results show that the system can supply accurate and rapid gap measurements and thus can fulfill the design and operational objectives.

In this Letter, we investigate the correlation rate of a random sequence data set which is collected by RFID (Radio Frequency IDentification) readers in an indoor location. Using a passive RFID tag introduces reading error, which causes a loss of original data. From the question of how sensing errors of RFID readers affect the location prediction algorithm used for context awareness services at home, we analyze the correlation rate of a collected data set with respect to RFID reader-sensing error rate. Through our analysis, we conclude that the prediction accuracy can be better or worse than the one of the original data streams according to the error rate. We suggest that the reader specification has to be satisfied by the error boundary which is found in this work for the tolerant location prediction.

The research on displacement vector detection has gained increasing attention in recent years. However, no relationship between displacement vectors and the outlines of objects in motion has been established. We describe a new method of detecting displacement vectors through edge segment detection by emphasizing the correlation between displacement vectors and their outlines. Specifically, after detecting an edge segment, the direction of motion of the edge segment can be inferred through the variation in the values of the Laplacian-Gaussian filter at the position near the edge segment before and after the motion. Then, by observing the degrees of displacement before and after the motion, the displacement vector can be calculated. The accuracy compared to other methods of displacement vector detection demonstrates the feasibility of this method.

This letter deals with computationally efficient maximum-likelihood (ML) detection for the quasi-orthogonal space-time block code (QOSTBC) with four transmit antennas. The proposed ML detector uses a permutation based real-valued equivalent channel matrix representation. As a result, the complexity of ML detection problem is moderated from O(2|A|2) to O(4|A|), where |A| is modulation order. Numerical results show that the proposed ML detector provides ML performance and achieves greatly high computational savings.

This paper presents a new interactive learning method for spoken word acquisition through human-machine audio-visual interfaces. During the course of learning, the machine makes a decision about whether an orally input word is a word in the lexicon the machine has learned, using both speech and visual cues. Learning is carried out on-line, incrementally, based on a combination of active and unsupervised learning principles. If the machine judges with a high degree of confidence that its decision is correct, it learns the statistical models of the word and a corresponding image category as its meaning in an unsupervised way. Otherwise, it asks the user a question in an active way. The function used to estimate the degree of confidence is also learned adaptively on-line. Experimental results show that the combination of active and unsupervised learning principles enables the machine and the user to adapt to each other, which makes the learning process more efficient.

This paper addresses the on-resistance (Ron) extraction of the DMOS based driver in Power IC designs. The proposed method can extract Ron of a driver from its layout data for the arbitrarily shaped metallization patterns. Such a driver is usually composed of arbitrarily shaped metals, arrayed vias, and DMOS transistors. We use FEM to extract the parasitic resistance of the source/drain metals since its strong contribution to Ron. In order to handle the large design case and accelerate the extraction process, a domain decomposition with virtual terminal insertion method is introduced, which succeeds in extraction for a set of industrial test cases including those the FEM without domain decomposition failed in. For a layout in which the DMOS cells are regularly placed, a sub-domain reuse procedure is also proposed, which obtained a dramatic speedup for the extraction. Even without the sub-domain reuse, our method still shows advantage in runtime and memory usage according to the simulation results.

In this paper, we propose a method that recovers a smooth high-resolution image from several blurred and roughly quantized low-resolution images. For compensation of the quantization effect we introduce measurements of smoothness, Huber function that is originally used for suppression of block noises in a JPEG compressed image [Schultz & Stevenson '94] and a smoothed version of total variation. With a simple operator that approximates the convex projection onto constraint set defined for each quantized image [Hasegawa et al. '05], we propose a method that minimizes these cost functions, which are smooth convex functions, over the intersection of all constraint sets, i.e. the set of all images satisfying all quantization constraints simultaneously, by using hybrid steepest descent method [Yamada & Ogura '04]. Finally in the numerical example we compare images derived by the proposed method, Projections Onto Convex Sets (POCS) based conventinal method, and generalized proposed method minimizing energy of output of Laplacian.

A wireless transceiver utilizing inductive coupling has been proposed for communication between chips in system in a package. This transceiver can achieve high-speed communication by using two-dimensional channel arrays. To increase the total bandwidth in the channel arrays, the density of the transceiver should be improved, which means that the inductor size should be scaled down. This paper discusses the scaling theory based on a constant magnetic field rule. By decreasing the chip thickness with the process scaling of 1/α, the inductor size can be scaled to 1/α and the data rate can be increased by α. As a result, the number of aggregated channels can be increased by α2 and the aggregated data bandwidth can be increased by α3. The scaling theory is verified by simulations and experiments in 350, 250, 180, and 90 nm CMOS.

Multi-carrier code division multiple access (MC-CDMA) has been considered as one of the promising techniques for the next generation of mobile communication systems because of its efficient bandwidth usage, robustness to the multi-path fading and simple channel-sharing scheme. However, MC-CDMA cannot be employed in the uplink communication where the transmitted signal from each user propagates through the different multi-path fading channel, and the received signals are no longer orthogonal at the base station. As a result, bit error rate (BER) performance in the uplink MC-CDMA communication would be strongly degraded due to the occurrence of multi-user interference (MUI). To solve the MUI problem in the uplink MC-CDMA, the pre-equalization method was proposed in which the uplink signal is pre-equalized at the user terminal by using the channel response estimated from the downlink. Although the pre-equalization method is very effective for the stationary uplink channel with fixed users, it is hard to be employed in the time varying fading channel with mobile users, because there is a big difference in the channel responses between downlink and uplink. For the efficient MUI compensation, each user terminal would be required to predict the future channel conditions based on the current observation. This paper proposes a method for model based uplink channel response prediction by employing the spectral decomposition of the downlink channel impulse response. Computer simulation results show that the proposed method can achieve the accurate prediction of channel response for mobile users during the uplink transmission and allows the effective MUI compensation.

Though machine vision systems for automatically detecting visual defects, called mura, have been developed for thin flat transistor liquid crystal display (TFT-LCD) panels, they have not yet reached a level of reliability which can replace human inspectors. To establish an objective criterion for identifying real defects, some index functions for quantifying defect levels based on human perception have been recently researched. However, while these functions have been verified in the laboratory, further consideration is needed in order to apply them to real systems in the field. To begin with, we should correct the distortion occurring through the capturing of panels. Distortion can cause the defect level in the observed image to differ from that in the panel. There are several known methods to restore the observed image in general vision systems. However, TFT-LCD panel images have a unique background degradation composed of background non-uniformity and vignetting effect which cannot easily be restored through traditional methods. Therefore, in this paper we present a new method to correct background degradation of TFT-LCD panel images using principal component analysis (PCA). Experimental results show that our method properly restores the given observed images and the transformed shape of muras closely approaches the original undistorted shape.

Effect of the post-growth annealing on the morphology of a Ge mesa selectively grown on Si was studied from the viewpoint of near-infrared photodiode applications. By ultrahigh-vacuum chemical vapor deposition, Ge mesas were selectively grown at 600 on Si (001) substrates partially covered with SiO2 masks. The as-grown Ge mesas showed trapezoidal cross-sections having a top (001) surface and {311} sidewall facets, as similar to previous reports. However, after the subsequent post-growth annealing at ~800 in the ultrahigh-vacuum chamber, the mesas were deformed into rounded shapes having a depression at the center and mounds near the edges. Such a deformation cannot be observed for the samples annealed once after cooled and exposed to the air. The residual hydrogen atoms on the Ge surface from the germane (GeH4) decomposition is regarded as a trigger to the observed morphological instability, while the final mesa shape is determined in order to minimize a sum of the surface and/or strain energies.

Combination of mutually complementary features is necessary to cope with various changes in pattern classification between normal and pathological voices. This paper proposes a method to improve pathological/normal voice classification performance by combining heterogeneous features. Different combinations of auditory-based and higher-order features are investigated. Their performances are measured by Gaussian mixture models (GMMs), linear discriminant analysis (LDA), and a classification and regression tree (CART) method. The proposed classification method by using the CART analysis is shown to be an effective method for pathological voice detection, with a 92.7% classification performance rate. This is a noticeable improvement of 54.32% compared to the MFCC-based GMM algorithm in terms of error reduction.