The authors propose a single-layer hollow-waveguide 8-way Butler matrix. All components of the Butler matrix are in a single layer which contributes to low-cost fabrication. To reduce the length of the couplers, a step structure is installed in the coupled region. 50% length reduction is obtained in comparison with the conventional design using reflection-suppressing posts in the coupled region. The total size of the matrix is 17.1λg6.0λg. The full structure of the matrix is fabricated by hollow waveguides at 22 GHz band and the total measured loss is only 0.25 dB.

Movement of the thighs is an important factor for studying gait cycle. In this paper, a hybrid hidden Markov model (HMM)/Kalman filter (KF) scheme is proposed to track the hip angle during gait cycles. Within such a framework, HMM and KF work in parallel to estimate the hip angle and detect major gait events. This approach has been applied to study gait features of different subjects and compared with video based approach. Experimental results indicate that 1.) the swing angle of the hip can be detected with simple hardware configuration using biaxial accelerometers and 2.) the hip angle can be tracked for different subjects within the error range of -5°+5°.

Developing embedded parallel image processing applications is usually a very hardware-dependent process, often using the single instruction multiple data (SIMD) paradigm, and requiring deep knowledge of the processors used. Furthermore, the application is tailored to a specific hardware platform, and if the chosen hardware does not meet the requirements, it must be rewritten for a new platform. We have proposed the use of design space exploration [9] to find the most suitable hardware platform for a certain application. This requires a hardware-independent program, and we use algorithmic skeletons [5] to achieve this, while exploiting the data parallelism inherent to low-level image processing. However, since different operations run best on different kinds of processors, we need to exploit task parallelism as well. This paper describes how we exploit task parallelism using an asynchronous remote procedure call (RPC) system, optimized for low-memory and sparsely connected systems such as smart cameras. It uses a futures [16]-like model to present a normal imperative C-interface to the user in which the skeleton calls are implicitly parallelized and pipelined. Simulation provides the task dependency graph and performance numbers for the mapping, which can be done at run time to facilitate data dependent branching. The result is an easy to program, platform independent framework which shields the user from the parallel implementation and mapping of his application, while efficiently utilizing on-chip memory and interconnect bandwidth.

In this paper, we proposed a new Two-Dimensional Linear Discriminant Analysis (2DLDA) method, based on Two-Dimensional Principle Component Analysis (2DPCA) concept. In particular, 2D face image matrices do not need to be previously transformed into a vector. In this way, the spatial information can be preserved. Moreover, the 2DLDA also allows avoiding the Small Sample Size (SSS) problem, thus overcoming the traditional LDA. We combine 2DPCA and our proposed 2DLDA on the Two-Dimensional Linear Discriminant Analysis of principle component vectors framework. Our framework consists of two steps: first we project an input face image into the family of projected vectors via 2DPCA-based technique, second we project from these space into the classification space via 2DLDA-based technique. This does not only allows further reducing of the dimension of feature matrix but also improving the classification accuracy. Experimental results on ORL and Yale face database showed an improvement of 2DPCA-based technique over the conventional PCA technique.

We developed a system that detects the vehicle driving immediately ahead of one's own car in the same lane and measures the distance to and relative speed of that vehicle to prevent accidents such as rear-end collisions. The system is the first in the industry to use non-scanning millimeter-wave radar combined with a sturdy stereo image sensor, which keeps cost low. It can operate stably in adverse weather conditions such as rain, which could not easily be done with previous sensors. The system's vehicle detection performance was tested, and the system can correctly detect vehicles driving 3 to 50 m ahead in the same lane with higher than 99% accuracy in clear weather. Detection performance in rainy weather, where water drops and splashes notably degraded visibility, was higher than 90%.

This paper deals with a secret key agreement problem from correlated random numbers. It is proved that there is a pair of linear matrices that yields a secret key agreement in the situation wherein a sender, a legitimate receiver, and an eavesdropper have access to correlated random numbers. A relation between the coding problem of correlated sources and a secret key agreement problem from correlated random numbers are also discussed.

This paper presents high-performance millimeter-wave passive devices using MEMS technology. The purpose of this paper is to show the possibility of MEMS technology as an enabling technology for millimeter-waves. The loss and cost issues, which have been the inherent barrier for commercialization of mm-waves, can be solved by RF MEMS technology. Successful demonstrations of MEMS technology for mm-waves include novel CPW transmission lines, digital impedance tuners, analog tunable band-pass filters, reconfigurable low-pass filters, V-band digital distributed phase shifters and 2-D mechanical beam-steering antennas. All these circuits were implemented for 30-65 GHz frequency range, and show the state-of-the-art performance, which is beyond the limit set by the conventional technology.

This paper deals with questions concerning the supply of building-blocks (BBs) in the initial population of real-coded genetic algorithms (rGAs). Drawing upon the methodology of existing BB supply studies for finite alphabets, facetwise models for the supply of a single schema as well as for the supply of all the schemata in a partition are proposed. A model for the initial population size necessary to ensure the presence of all the raw BBs with a given supply error has also been developed using the partition success model. Experimental results show the effectiveness of the facetwise models and the initial population sizing model. Finally, an adaptation approach is suggested for practical use of the BB supply.

In AlGaN/GaN high electron mobility transistors (HEMTs), Si3N4 passivation film brings effective improvements in the current collapse phenomenon, however, the suppression of this phenomenon in a high voltage operation can not be achieved in only the Si3N4 deposition process. In order to solve this problem, we have demonstrated an NH3-plasma surface pretreatment in the chamber of plasma enhanced chemical vapor deposition (PE-CVD) just before Si3N4 deposition process. We found that the optimized NH3-plasma pretreatment could improve the current collapse as compared with only the Si3N4 deposition and an excessive pretreatment made it worse adversely in AlGaN/GaN-HEMTs. It was confirmed by Auger electron spectroscopy (AES) analysis that the optimized NH3-plasma pretreatment decreased the carbon contamination such as hydrocarbon on the AlGaN surface and the excessive pretreatment degraded the stoicheiometric composition of AlGaN surface.

The noise robustness of an audio fingerprinting system is one of the most important issues in music information retrieval by the content-based audio identification technique. In a real environment, sound recordings are commonly distorted by channel and background noise. Recently, Philips published a robust and efficient audio fingerprinting system for audio identification. To extract a robust and efficient audio fingerprint, Philips applied the first derivative (differential) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the noise robustness of Philips' audio fingerprinting scheme is still insufficient. In this paper, we introduce an extension method of the audio fingerprinting scheme for the enhancement of noise robustness. As an alternative to frequency filtering, a type of band-pass filter, instead of a high-pass filter, is used to achieve robustness to background noise in a real situation. Our experimental results show that the proposed filter improves the noise robustness in audio identification.

This paper presents a view independent video-based face recognition method using posterior probability in Kernel Fisher Discriminant (KFD) space. In practical environment, the view of faces changes dynamically. Robustness to view changes is required for video-based face recognition in practical environment. Since the view changes induce large non-linear variation, kernel-based methods are appropriate. We use KFD analysis to cope with non-linear variation. To classify image sequence, the posterior probability in KFD space is used. KFD analysis assumes that the distribution of each class in high dimensional space is Gaussian. This makes the computation of posterior probability in KFD space easy. The combination of KFD space and posterior probability of image sequence is the main contribution of the proposed method. The performance is evaluated by using two face databases. Effectiveness of the proposed method is shown by the comparison with the other feature spaces and classification methods.

In this paper, we report a manufacturable InP DHBT technology, suitable for medium scale mixed-signal and monolithic microwave integrated circuits. The InGaAs/InP DHBTs were grown by MBE and fabricated using conventional process techniques. Devices with an emitter junction area of 4.8 µm2 exhibited peak cutoff frequency (fT) and maximum oscillation frequency (fMAX) values of 265 and 305 GHz, respectively, and a breakdown voltage (BVCEo) of over 5 V. Using this technology, a set of mixed-signal IC building blocks for ≥ 80 Gbit/s fibre optical links, including distributed amplifiers (DA), voltage controlled oscillators (VCO), and multiplexers (MUX), have been successfully fabricated and operated at 80 Gbit/s and beyond.

This paper studies bit-interleaved coded modulation with iterative decoding (BICM-ID) systems that employ multi-dimensional mappings of M-ary constellations to improve the error performance over Rayleigh fading channels. Based on the analytical evaluations of the asymptotic bit error probability (BEP), the distance criteria for the mapping designs can be obtained. A binary switching algorithm (BSA) is then applied to find the optimal mappings with respect to the asymptotic performance. Simulation and analytical results show that the use of multi-dimensional mappings of M-ary constellations can significantly improve the error performance.

Coexisting with many concurrent narrowband services, the performance of UWB systems will be affected considerably by them. Specifically, IEEE 802.11a systems which operate around 5 GHz and overlap the band of UWB signals will interfere with UWB systems significantly. In this paper, a novel narrow-band interferences (NBI) suppression technique based on singular value decomposition (SVD) algorithm for a direct sequence ultra-wideband (DS-UWB) communication system is presented. SVD is used to approximate the interferences which then are subtracted from the received signals. The proposed technique is simple and robust. Simulation results show that the proposed new technique is very effective.

In this letter we present steady-state analyses of a gradient algorithm (GA) for second-order adaptive infinite impulse response (IIR) notch filters. A method for deriving more accurate estimation mean square error (MSE) expressions than the recently proposed method is presented. The method is based on the estimation error power spectral density (PSD). Moreover, an expression for the estimation bias for the adaptive IIR notch filter with constrained poles and zeros is shown to be obtained from the estimation MSE expression. Simulations are presented to confirm the validity of the analyses.

Wavelength division multiplexing (WDM) technology offers the capability of building wide-area networks with high speed. Reconfigurability is a key feature of a WDM network that enables the network logical topology to change dynamically in response to the changing traffic patterns. There are two important issues involved in the reconfiguration of a network logical topology. One is how to determine the new logical topology corresponding to the current topology. It needs to consider a trade-off between the performance of the new target topology and the cost of the topology transition from the current topology to the new one. The other is how to determine the transition sequence from the current topology to the new one. It needs to control the disruption to the network as less as possible during the reconfiguration process. In this paper, we focus on the latter problem and propose several heuristic algorithms that reconfigure logical topologies in wide-area wavelength-routed optical networks. Our reconfiguration algorithms attempt to control the disruption to the network as less as possible during the reconfiguration process. For this purpose, a lightpath is taken as the minimum reconfiguration unit. The proposed algorithms are evaluated by using an NFSNET-like network model with 16 nodes and 25 links. The results show that very simple algorithms provide very small computational complexity but poor performance, i.e., large network disruption, and that an efficient algorithm provides reasonable computational complexity and very good performance. More complex algorithms may improve performance somewhat further but have unrealistically large computational complexity.

A new method for automatically building statistical shape models from a set of training examples and in particular from a class of hands. In this study, we utilise a novel approach to automatically recover the shape of hand outlines from a series of 2D training images. Automated landmark extraction is accomplished through the use of the self-organising model the growing neural gas (GNG) network, which is able to learn and preserve the topological relations of a given set of input patterns without requiring a priori knowledge of the structure of the input space. The GNG is compared to other self-organising networks such as Kohonen and Neural Gas (NG) maps and results are given for the training set of hand outlines, showing that the proposed method preserves accurate models.

This paper discusses a cyclic prefixed single carrier frequency-domain equalization (SC-FDE) scheme with two types of transmit diversity. Firstly, we propose a SC-FDE system with space-frequency block coding (SFBC). The transmit sequence of the proposed system is designed to have spatial and frequency diversities, which is equivalent to the SFBC. The corresponding combining receiver is derived under a minimum mean square error (MMSE) criterion. It is shown that the proposed system significantly outperforms the SC-FDE system with space-time block coding (STBC) over fast fading channels, while providing lower computational complexity than orthogonal frequency division multiplexing (OFDM) combined with SFBC. We verify the performance of two-branch transmit diversity systems including the proposed one through bit error rate (BER) analysis. Secondly, as a scheme that combines STBC and SFBC, a space-time-frequency block code (STFBC) SC-FDE system is presented. Computer simulation results show that the proposed STFBC SC-FDE system has better immunity to the distortion caused by both fast fading and severe frequency selective fading, compared to the SC-FDE system with the STBC or the SFBC scheme. Complexity analysis is also conducted to compare their computational loads of the transceiver. It is shown that the proposed STFBC SC-FDE system has lower computational complexity than the STFBC OFDM system.

We present room temperature current voltage characteristics from SiGe interband tunneling diodes epitaxially grown on highly resistive Si(001) substrates. In this case, a maximum peak to valley current ratio (PVCR) of 5.65 was obtained. The possible integration of a SiGe tunnel diode with a strained Si transistor lead us to investigate the growth of SiGe interband tunneling diodes on Si0.7Ge0.3 virtual substrates. A careful optimization of the layer structure leads to a maximum PVCR of 1.36 at room temperature. The latter value can be further increased to 2.26 at 3.7 K. Our results demonstrate that high quality SiGe interband tunneling diodes can be realized, which is of great interest for future memory and high speed applications.

Kernel-based learning algorithms have been successfully applied in various problem domains, given appropriate kernel functions. In this paper, we discuss the problem of designing kernel functions for binary regression and show that using a bell-shaped cosine function as a kernel function is optimal in some sense. The rationale of this result is based on the Karhunen-Loeve expansion, i.e., the optimal approximation to a set of functions is given by the principal component of the correlation operator of the functions.