This paper reviews the historical development of adaptive antennas in Japan. First of all, we watch basic adaptive algorithms. In 1980s, particularly, the following issues were a matter of considerable concern to us; (a) behavior to the coherent interference like multipath waves or radar clutters, (b) signal degradation in case that the direction of arrival (DOA) of desired signal is different from the DOA specified beforehand in the adaptive antennas with the DOA of the desired signal as a prior knowledge, and (c) performance of adaptive antennas when the desired signal and interference are broadband. Although there are a lot of development and modification of adaptive algorithms in Japan, we refer in this paper only to the above-mentioned topics. Secondly, our attention is paid to implementation of adaptive antennas and advanced technologies. A large number of researches on the subjects have been carried out in Japan. Particularly, we focus on the initiative studies in Japan toward mobile communication application. They include researches of mobile radio propagation for adaptive antennas, calibration methods, and adaptive antenna for mobile terminals. As a matter of course, we also refer to adaptive antenna technologies for advanced communication schemes such as CDMA, SDMA, OFDM and so on. Finally, we take notice of some pilot products which were developed to verify the effect of the adaptive antenna in the practical environments. As the initiative ones, a couple of equipments are introduced in this paper.

The effect of a conductive sheet placed over a PCB with a microstrip line on electromagnetic noise shielding is investigated. As a typical conductive sheet, a copper sheet is used, and is not grounded. First, the input impedance of the microstrip line and the magnetic field when varying the distance between the PCB and the conductive sheet are measured, and the distance that does not affect the signal transmission is set at 8 mm. Second, the effect of the conductive sheet size on the magnetic field radiation is discussed by measurements and FDTD modeling, and the magnetic near-field distribution around the PCB is visualized by using the FDTD calculation. A conductive sheet whose width is larger than the PCB width should be effective for suppression of the magnetic near-field noise radiation just above a PCB.

A two-qubit system made of electrons running along coupled pairs of quantum wires is described and numerically analyzed. A brief review of the basic gates is given first, based on preliminary investigations, followed by the description of the electron dynamics. A detailed analysis of a conditional phase shifter is carried out by means of a time-dependent Schrodinger solver applied to a two-particle system. A quantum network suitable for creating entanglement is simulated, and results are shown. The physical structure of the proposed network is within the reach of a solid-state implementation. The physical parameters used in the computations have been chosen with reference to silicon quantum wires embedded in silicon dioxide.

In the last three decades of the 20th Century, research in speech recognition has been intensively carried out worldwide, spurred on by advances in signal processing, algorithms, architectures, and hardware. Recognition systems have been developed for a wide variety of applications, ranging from small vocabulary keyword recognition over dial-up telephone lines, to medium size vocabulary voice interactive command and control systems for business automation, to large vocabulary speech dictation, spontaneous speech understanding, and limited-domain speech translation. Although we have witnessed many new technological promises, we have also encountered a number of practical limitations that hinder a widespread deployment of applications and services. On one hand, fast progress was observed in statistical speech and language modeling. On the other hand only spotty successes have been reported in applying knowledge sources in acoustics, speech and language science to improving speech recognition performance and robustness to adverse conditions. In this paper we review some key advances in several areas of speech recognition. A bottom-up detection framework is also proposed to facilitate worldwide research collaboration for incorporating technology advances in both statistical modeling and knowledge integration into going beyond the current speech recognition limitations and benefiting the society in the 21st century.

We propose a minimal model of neuronal burst-firing that can be considered as a modification and extention of the Bonhoeffer-van der Pol (BVP) model. By using linear stability analysis we show that one of the equilibrium points of the fast subsystem is a saddle point which divides the phase plane into two regions. In one region all phase trajectories approach a limit cycle and in the other they approach a stable equilibrium point. The slow subsystem describes a slowly varying inward current. Various types of bursting phenomena are presented by using bifurcation analysis. The simplicity of the model and the variety of firing modes are the biggest advantages of our model with obvious applications in understanding underlying mechanisms of generation of neuronal firings and modeling oscillatory neural networks.

This paper derives a set of orthogonal polynomials for a complex random variable that is uniformly distributed in two dimensions (2D). The polynomials are used in a series expansion to approximate memoryless nonlinearities in digital QAM systems. We also study stochastic identification of nonlinearities using the orthogonal polynomials through analysis and simulations.

We propose a new algorithm for blind source separation (BSS), in which independent component analysis (ICA) and beamforming are combined to resolve the low-convergence problem through optimization in ICA. The proposed method consists of the following two parts: frequency-domain ICA with direction-of-arrival (DOA) estimation, and null beamforming based on the estimated DOA. The alternation of learning between ICA and beamforming can realize fast- and high-convergence optimization. The results of the signal separation experiments reveal that the signal separation performance of the proposed algorithm is superior to that of the conventional ICA-based BSS method.

A TCAD implementation of a quantum-mechanical mobility model in the commercial device simulator DESSIS_ISE is presented. The model makes use of an integrated 1D Schrodinger-Poisson solver. Effective mobilities µeff and transfer characteristics are calculated for DGSOI MOSFETs with a wide range of silicon film thickness tSi and buried-oxide thickness tbox. It is shown that the volume-inversion related enhancement of µeff for tSi 10 nm is bound to symmetrical DGSOIs, whereas SIMOX based devices with thick buried oxides limit µeff to the bulk value. The still immature technology makes a conclusive comparison with experimental data impossible.

A new blind identification method of transfer functions between variables in feedback systems is introduced for single sweep type of MEG data. The method is based on the viewpoint of stochastic/statistical inverse problems. The required conditions of the model are stationary and linear Gaussian processes. Raw MEG data of the brain activities are heavily contaminated with several noises and artifacts. The elimination of them is a crucial problem especially for the method. Usually, these noises and artifacts are removed by notch and high-pass filters which are preset automatically. In the present paper, we will try two types of more careful preprocessing procedures for the identification method to obtain impulse functions. One is a careful notch filtering and the other is a blind source separation method based on temporal structure. As results, identifiably of transfer functions and their impulse responses are improved in both cases. Transfer functions and impulse responses identified between MEG sensors are obtained by using the method in Appendix A, when eyes are closed with rest state. Some advantages of the blind source separation method are discussed.

Music style is one of the features that people used to classify music. Discovery of music style is helpful for the design of content-based music retrieval systems. In this paper we investigated the mining and classification of music style by melody from a collection of MIDI music. We extracted the chord from the melody and investigated the representation of extracted features and corresponding mining techniques for music classification. Experimental results show that the classification achieved 64% to 84% accuracy for two-way classification.

An atomistic model for annealing simulation is presented. To well simulate both BED (Boron Enhanced Diffusion) and TED (Transient Enhanced Diffusion), the surface emission model, which describes the emission of point defects from surface during annealing, is implemented. The simulation is carried out for RTA annealing (1000 or 1050) after B implantation. The implantation energy varies from 0.5 keV to 13 keV. Agreements between simulation and SIMS data are achieved. Both BED and TED phenomena are characterized. The Enhancement of diffusion is discussed. The surface emission model is studied by simulation. The results shows that the surface emission has little effect on annealing of B 10 keV implantation while obvious effect on annealing of B 0.5 keV implantation. It indicates that the surface emission is much more necessary to simulate BED than TED.

Though, high dielectric constant material is a possible near future solution in order to suppress gate current densities of MOSFETs, the barrier height generally decreases with an increasing dielectric constant. In this paper, the injection current through gate stacks has been calculated while taking into account the electron temperature using the W.K.B. method to understand the impact of the injection current from the drain edge.

RF noise in quarter-micron nMOSFETs is analysed on the device level based on Shockley's impedance field method. The impact of different transport models and physical parameters is discussed in detail. Well-calibrated drift-diffusion and energy-balance models give very similar results for noise current spectral densities and noise figures. We show by numerical simulations with the general-purpose device simulator DESSIS_ISE that the hot-electron effect on RF noise is unimportant under normal operating conditions and that thermal substrate noise is dominant below 0.5 GHz. The contribution of energy-current fluctuations to the terminal noise is found to be negligible. Application of noise sources generated in bulk full-band Monte Carlo simulations changes the noise figures considerably, which underlines the importance of proper noise source models for far-from-equilibrium conditions.

A high power dissipation density in today's miniature electronic/mechanical systems makes on-chip thermal management very important. In order to achieve quick to evaluate, yet accurate electro-thermal models, needed for the thermal management of microsystems, a model order reduction is necessary. In this paper, we present an automatic, Krylov-subspace-based order reduction of a electro-thermal model, which we illustrate by a novel type of micropropulsion device. Numerical simulation results of the full finite element model and the reduced order model, that describes the transient electro-thermal behavior, are presented. A comparison between Krylov-subspace-based order reduction, order reduction using control theoretical approaches and commercially available reduced order modeling has been performed. A Single-Input-Single-Output setup for the Arnoldi reduction algorithm was proved to be sufficient to accurately represent the complete time-dependent temperature distribution of the device.

A brief review is given on a crossover in transport between quantum and classical regimes due to the presence of inelastic scattering destroying the phase coherence. In the integer quantum Hall effect, the quantum regime corresponds to the edge-current picture and the classical to the bulk Hall current picture. The crossover between two regimes occurs through inelastic scattering. In a metallic carbon nanotube, there is a perfectly transmitting channel independent of energy for conventional scatterers having potential range larger than the lattice constant, making the nanotube a perfect conductor. When several bands coexist at the Fermi level, such a perfect channel is destroyed by inelastic scattering.

The implant-anneal cycle for B doping during Si device fabrication causes transient enhanced diffusion (TED) of B and the formation of small immobile B-interstitial clusters (BICs) which deactivate the B. Additionally, since modern ultrashallow devices put most of the B in immediate proximity of the Si/SiO2 interface, interface-dopant interactions like segregation become increasingly important. In this work, we use density-functional theory calculations to study TED, clustering, and segregation of B during annealing and discuss a continuum model which combines the TED and clustering results.

The validity and capability of an iterative coupling scheme between single-particle frozen-field Monte Carlo simulations and nonlinear Poisson solutions for achieving self-consistency is investigated. For this purpose, a realistic 0.1 µm lightly-doped-drain (LDD) n-MOSFET with a maximum doping level of about 2.5 1020 cm-3 is simulated. It is found that taking the drift-diffusion (DD) or the hydrodynamic (HD) model as initial simulation leads to the same Monte Carlo result for the drain current. This shows that different electron densities taken either from a DD or a HD simulation in the bulk region, which is never visited by Monte Carlo electrons, have a negligible influence on the solution of the Poisson equation. For the device investigated about ten iterations are necessary to reach the stationary state after which gathering of cumulative averages can begin. Together with the absence of stability problems at high doping levels this makes the self-consistent single-particle approach (SPARTA) a robust and efficient method for the simulation of nanoscale MOSFETs where quasi-ballistic transport is crucial for the on-current.

Impact ionization and thermionic tunnelling as two possible breakdown mechanisms in scaled pseudomorphic high electron mobility transistors (PHEMTs) are investigated by Monte Carlo (MC) device simulations. Impact ionization is included in MC simulation as an additional scattering mechanism whereas thermionic tunnelling is treated in the WKB approximation during each time step in self-consistent MC simulation. Thermionic tunnelling starts at very low drain voltages but then quickly saturates. Therefore, it should not drastically affect the performance of scaled devices. Impact ionization threshold occurs at greater drain voltages which should assure a reasonable operation voltage scale for all scaled PHEMTs.

Monte Carlo simulation of the low field electron mobility of strained Si and SiGe active layers on Si and SiGe substrates is considered. The Ge mole fractions of both the active layer and the substrate are varied in a wide range. The linear deformation potential theory is used to calculate the shifts of the conduction band minima due to uniaxial strain along [001]. The energy shifts and the effective masses are assumed to be functions of the Ge mole fraction. It is shown that in spite of the fact that the L-valleys remain degenerate under strain conditions considered here, they play an important role at very high Ge compositions especially when SiGe as substrate is used. We found that in this case the repopulation effects of the X-valleys affect electron mobility much stronger than the alloy scattering. We also generalize the ionized impurity scattering rate to include strain effects for doped materials and show that some of the important parameters such as effective density of states, inverse screening length, and the screening function are split due to strain and must be properly modified. Finally, we perform several simulations for undoped and doped materials using Si and SiGe substrates.

The density gradient (DG) model is tested for its ability to describe tunneling currents through thin insulating barriers. Simulations of single barriers (MOS diodes, MOSFETs) and double barriers (RTDs) show the limitations of the DG model. For comparison, direct tunneling currents are calculated with the Schrodinger-Bardeen method and used as benchmark. The negative differential resistance (NDR) observed in simulating tunneling currents with the DG model turns out to be an artifact related to large density differences in the semiconductor regions. Such spurious NDR occurs both for single and double barriers and vanishes, if all semiconductor regions are equally doped.