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.

Nowadays, silicon technologies with feature sizes around 100 nm are used in the microelectronics industry to produce gigabits integrated circuits. The prime part of numerical simulation in their development is now well established. One of the purpose of the numerical analyses is the improvement of the mechanical reliability. We synthetize in this paper various works we have performed on the macroscopical modeling and simulation of stress problems and their effects in silicon technologies.

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.

This paper concerns recognizing 3-dimensional object using proposed multi-layer block model. In particular, we aim to achieve desirable recognition performance while restricting the computational load to a low level using 3-step feature extraction procedure. An input image is first precisely partitioned into hierarchical layers of blocks in the form of base blocks and overlapping blocks. The hierarchical blocks are merged into a matrix, with which abundant local feature information can be obtained. The local features extracted are then employed by the kernel based support vector machines in tournament for enhanced system recognition performance while keeping it to low dimensional feature space. The simulation results show that the proposed feature extraction method reduces the computational load by over 80% and preserves the stable recognition rate from varying illumination and noise conditions.

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.

In this work it is shown for the first time how to calculate in advance by momentum-based noise simulation for stationary Monte Carlo (MC) device simulations the CPU time, which is necessary to achieve a predefined error level. In addition, analytical expressions for the simulation-time factor of terminal current estimation are given. Without further improvements of the MC algorithm MC simulations of small terminal currents are found to be often prohibitively CPU intensive.

It is well known that KT method proposed by R. Kumaresan and D. W. Tufts is used as a popular parameter estimation method of exponentially damped signal. It is based on linear backward-prediction method and singular value decomposition (SVD). However, it is difficult to estimate parameters correctly by KT method in the case when high noise exists in the signal. In this paper, we propose a parameter (frequency components and damping factors) estimation method to improve the performance of KT method under high noise. In our proposed method, we find the signal zero groups by calculating zeros with different data record lengths according to the combination of forward-prediction and backward-prediction, the mean value of the zeros in the signal zero groups are calculated to estimate the parameters of the signal. The proposed method can estimate parameters correctly and accurately even when high noise exists in the signal. Simulation results are shown to confirm the effectiveness of the proposed method.

An adaptive array antenna for the suppression of high-power interference in direct-sequence code-division multiple access (DS-CDMA) systems is presented. Although DS-CDMA has sufficient flexibility to support a variety of services, from voice to moving-pictures, with high levels of quality, multiple access interference (MAI) is a problem. This is particularly so of the high-power interference which accompanies high-speed transmission in DS-CDMA. While the application of adaptive array antennas is an effective way of improving signal-to-interference-plus-noise ratio (SINR), problems with this approach include large levels of power consumption and the high costs of hardware and of implementing the antennas. Therefore, our main purpose is to realize a simple configuration for an adaptive array system. In order to reduce the required amounts of processing, a common beam provides suppression of high-power interference for the low-bit-rate users; this makes per-user preparation of weights unnecessary. This approach also reduces the consumption of power by the system. Interference is cancelled by minimization of the array output power (i.e., the application of a power inversion algorithm) before despreading. The approach also allows us to improve the implementation of the antenna elements by using small auxiliary antennas. The basic performance of the system is confirmed through numerical calculation and computer simulation. Furthermore, a real-time processing unit has been developed and the effectiveness of the approach is confirmed by an experiment in a radio-anechoic chamber.

In this paper, a novel approach to speaker recognition is proposed. The approach makes use of adaptive boosting (AdaBoost) and classifiers such as Multilayer Perceptrons (MLP) and C4.5 Decision Trees for closed set, text-dependent speaker recognition. The performance of the systems is assessed using a subset of utterances drawn from the YOHO speaker verification corpus. Experiments show that significant improvement in accuracy can be achieved with the application of adaptive boosting techniques. Results also reveal that an accuracy of 98.8% for speaker identification may be achieved using the adaptively boosted C4.5 system.

This paper reviews the antenna system for Japanese celullar systems and PHS (Personal Handphone System). The unique features of the Japanese cellualr system are multi-band operation, compact diversity antennas, electronic beam tilting, and indoor booster systems. The original antennas for the above purpose will be described. The PHS is also a unique mobile communication system in Japan, and is mainly used for high speed, low cost data transmission. Its original antennas are also presented in this paper.

Blind separation of sources from their linear mixtures is a well understood problem. However, if the mixtures are nonlinear, this problem becomes generally very difficult. This is because both the nonlinear mapping and the underlying sources must be learned from the data in a blind manner, and the problem is highly ill-posed without a suitable regularization. In our approach, multilayer perceptrons are used as nonlinear generative models for the data, and variational Bayesian (ensemble) learning is applied for finding the sources. The variational Bayesian technique automatically provides a reasonable regularization of the nonlinear blind separation problem. In this paper, we first consider a static nonlinear mixing model, with a successful application to real-world speech data compression. Then we discuss extraction of sources from nonlinear dynamic processes, and detection of abrupt changes in the process dynamics. In a difficult test problem with chaotic data, our approach clearly outperforms currently available nonlinear prediction and change detection techniques. The proposed methods are computationally demanding, but they can be applied to blind nonlinear problems of higher dimensions than other existing approaches.

In this study, we introduce a method for estimating the syntactic structure of Japanese speech from F0 contour and pause duration. We defined a prosodic unit (PU) which is divided by the local minimal point of an F0 contour or pause. Combining PUs repeatedly (a pair of PUs is combined into one PU), a tree structure is gradually generated. Which pair of PUs in a sequence of three PUs should be combined is decided by a discriminant function based on the discriminant analysis of a corpus of speech data. We applied the method to the ATR Phonetically Balanced Sentences read by four Japanese speakers. We found that with this method, the correct rate of judgement for each sequence of three PUs is 79% and the estimation accuracy of the entire syntactic structure for each sentence is 26%. We consider this result to demonstrate a good degree of accuracy for the difficult task of estimating syntactic structure only from prosody.

This paper presents a method of temporal decomposition (TD) for line spectral frequency (LSF) parameters, called "Modified Restricted Temporal Decomposition" (MRTD), and its application to low rate speech coding. The LSF parameters have not been used for TD due to the stability problems in the linear predictive coding (LPC) model. To overcome this deficiency, a refinement process is applied to the event vectors in the proposed TD method to preserve their LSF ordering property. Meanwhile, the restricted second order TD model, where only two adjacent event functions can overlap and all event functions at any time sum up to one, is utilized to reduce the computational cost of TD. In addition, based on the geometric interpretation of TD the MRTD method enforces a new property on the event functions, named the "well-shapedness" property, to model the temporal structure of speech more effectively. This paper also proposes a method for speech coding at rates around 1.2 kbps based on STRAIGHT, a high quality speech analysis-synthesis method, using MRTD. In this speech coding method, MRTD based vector quantization is used for encoding spectral information of speech. Subjective test results indicate that the speech quality of the proposed speech coding method is close to that of the 4.8 kbps FS-1016 CELP coder.

We propose two modifications of Gaussian processes, which aim to deal with dynamic environments. One is a weight decay method that gradually forgets old data, and the other is a time stamp method that regards the time course of data as a Gaussian process. We show experimental results when these modifications are applied to regression problems in dynamic environments. The weight decay method is found to follow the environmental change by automatically ignoring the past data, and the time stamp method is found to predict linear alteration.

A realistic 3-D process/device simulation method was developed for investigating the fluctuation in device characteristics induced by the statistical nature of the number and position of discrete dopant atoms. Monte Carlo procedures are applied for both ion implantation and dopant diffusion/activation simulations. Atomistic potential profile for device simulation is calculated from discrete dopant atom positions by incorporating the long-range part of Coulomb potential. This simulation was used to investigate the variations in characteristics of sub-100 nm CMOS devices induced by realistic dopant fluctuations considering practical device fabrication processes. In particular, sensitivity analysis of the threshold voltage fluctuation was performed in terms of the independent dopant contribution, such as that of the dopant in the source/drain or channel region.

This paper proposes a silence compression algorithm operating at multi-rates (MR) and with dual-bandwidths (DB), a narrowband and a wideband, for the MPEG (Moving Picture Experts Group)-4 CELP (Code Excited Linear Prediction) standard. The MR/DB operations are implemented by a Variable-Frame-size/Dual-Bandwidth Voice Activity Detection (VF/DB-VAD) module with bandwidth conversions of the input signal, and a Variable-Frame-size Comfort Noise Generator (VF-CNG) module. The CNG module adaptively smoothes the Root Mean Square (RMS) value of the input signal to improve the coding quality during transition periods. The algorithm also employs a Dual-Rate Discontinuous Transmission (DR-DTX) module to reduce an average transmission bitrate during silence periods. Subjective test results show that the proposed silence compression algorithm gives no degradation in coding quality for clean and noisy speech signals. These signals include about 20 to 30% non-speech frames and the average transmission bitrates are reduced by 20 to 40%. The proposed algorithm has been adopted as a part of the ISO/IEC MPEG-4 CELP version 2 standard.

New physical models, algorithms, and parameters are needed to accurately model emerging silicon-on-insulator (SOI) devices. The modeling approaches for various emerging SOI technologies are discussed in this paper.

It is still an open problem to elucidate the scaling merits of an embedded SRAM with Low Operating Power (LOP) MOSFETs fabricated in 50, 70 and 100 nm CMOS technology nodes. Taking into account a realistic SRAM cell layout, we evaluated the parasitic capacitance of the bit line (BL) as well as the word line (WL) in each generation. By means of a 3-Dimensional (3D) interconnect simulator (Raphael), we focused on the scaling merit through a comparison of the simulated SRAM BL delay for each CMOS technology node. In this paper, we propose two kinds of original interconnect structure which modify ITRS (International Technology Roadmap for Semiconductors), and make it clear that the original interconnect structures with reduced gate overlap capacitance guarantee the scaling merits of SRAM cells fabricated with LOP MOSFETs in 50 and 70 nm CMOS technology nodes.

The design criteria for space-time trellis codes (STTC's) in fast fading channels have been proposed: the Distance Criterion and the Product Criterion. The design criteria in [1] are based on optimizing the pairwise error probability (PWEP). However, the frame error rate (FER) of STTC's depends on the distance spectrum. In this paper, we propose a new design criterion for STTC's based on the distance spectrum in fast fading channels. The proposed design criterion is based on the product distance distribution for the large signal-to-noise ratio (SNR) and the trace distribution for the small SNR, respectively. Moreover, we propose new STTC's by the computer search based on the proposed design criterion in fast fading channels. By computer simulation, we show that the proposed design criterion is more useful than the Product Criterion in [1] in fast fading channels. We also show that the proposed STTC's achieve better FER than the conventional STTC's in fast fading channels.

New algorithms for the soft-decision and the hard-decision maximum likelihood decoding (MLD) for binary linear block codes are proposed. It has been widely known that both MLD can be regarded as an integer programming with binary arithmetic conditions. Recently, Conti and Traverso have proposed an efficient algorithm which uses Grobner bases to solve integer programming with ordinary integer arithmetic conditions. In this paper, the Conti-Traverso algorithm is extended to solve integer programming with modulo arithmetic conditions. We also show how to transform the soft-decision and the hard-decision MLD to integer programming for which the extended Conti-Traverso algorithm is applicable.