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In this paper, we classify the human conditions (before and after meal, before and after smoking) and extract the frequency feature of conditions by using the electroencephalograms (EEG). First, we measure the EEG data. Then, we classify the conditions by using the principal component analysis (PCA). Moreover, the EEG data is reconstructed by using the questionnaires and the result of classification. From the result, we consider ideal circumstance for the EEG measurement. Finally, the EEG data is decompressed to consider the EEG features of conditions. Then, in order to show the effectiveness of the proposed method, computer simulations are done.

In this paper, we propose the detection system of the human activity by using the electroencephalograms (EEG). First, we measure the EEG data for subjects. In most of all conventional studies, the EEG having a lot of sensors is used. Therefore, subjects must eat or smoke while using the EEG interface. However, this situation is not practical for subjects. In this study, taking account of the burden of subjects, we use only one measurement point 'FPI'. First, we measure the EEG data and the EMG data for subjects. Then, the EEG feature is extracted by using the singular value decomposition (SVD). From the result, we classify the EEG pattern by the fuzzy c-means (FCM). If we cannot classify the EEG pattern into each activity, the discriminant analysis (DA) is used. We consider the EEG features of activities. Then, in order to show the effectiveness of the proposed method, computer simulations are done.

The paper deals with the proposal of a combination system of time-delayed diversity (TDD) and satellite diversity (Sat. D) (TDD/Sat.D system) for a mobile broadcasting geostationary satellite system. The characteristics measurements of fundamental elements are carried out using Global Positioning System (GPS) signals. Prior to examining the TDD/Sat.D system, the measured TDD and Sat.D systems data are summarized. Based on the collected data, it can be clarified that approximately 40% satellite visibility without the Sat.D or TDD systems can be improved to approximately 70-80%. However, better satellite visibilities will be required for high quality data communication or image communication systems. On considering the measured results of the TDD and Sat.D system characteristics, the paper propose the TDD/Sat.D system. Using the TDD/Sat.D system, satellite visibility for target signals in urban cities can be remarkably improved.

The paper deals with the time delayed diversity (TDD) system characteristics for a quasi-zenith satellite system measured using GPS (Global Positioning System) satellites. To design a digital mobile broadcast satellite system with the TDD system, it must estimate the characteristics of attenuation by urban buildings, electrical light poles, trees, etc. Signal data from southern orbital arc GPS satellites with elevation angles from 40/spl deg/ to 80/spl deg/ are used for propagation characteristics measurements, rather than from actual geostationary satellite orbit (GSO) satellites. To overcome urban signal attenuation, the TDD system is applied for GSO satellites and quasi-zenith satellite systems and TDD characteristics are examined by processing measured GPS data.

Summary form only given. We have already proposed a desk-type contactless power supply (CLPS) using spiral-formed coils. In this system in order to supply electrical power efficiently to portable electric equipment on the desk, the primary coils are embedded into the surface of the desk. Only the coils beneath the secondary coil which is arranged at the bottom of the electric equipment are excited. We improved the configuration of primary and secondary coils and transmitted characteristics of electric supply and charging circuit.

The advanced high current ion implanter, the NV-GSD-HC3, has been developed to meet the requirements for 0.18 and 0.13 micron design rules of semiconductor manufacturing processes, especially for large size (300 mm, 200 mm) wafer processes and ultra-shallow junction processes. The following developments are incorporated in this system: an improved wafer handling system with very high throughput, high acceptance beam optics in the ultra low energy region by adopting the improved beam line from the NV-GSDIII system, charge neutralization system with plasma electron flood gun, improved long life ion source and advanced automatic control system.

As the design rule of semiconductor devices is shrinking, energy of ion implants is dramatically decreasing to make transistor junction depths shallower. The 0.5keV B+ and even 0.2keV B+ implants have been started to be used in volume production recently. However, productivity in such a low energy region is relatively low because of poor beam current due to difficulties of beam extraction and transport on ion implanter systems. The LEX is a next generation, ultra-low energy, high current ion implanter. This system has been developed to deliver production-worthy beam current even in the sub-keV region, employing newly designed beam optics and some new technologies which can reduce the so-called space charge effects. Significant increment of beam current has been achieved in the energy region below 10keV, needless to say, including the sub-keV region. For 300-mm wafer processing, the LEX3 also has been developed with the almost same beam-line and the same beam specification as the LEX. The system outlines, new technologies and performance of the LEX/LEX3 are described.

A method for constructing the reduced-rank Toeplitz approximation matrices to the linear prediction matrices of the covariance matrices is proposed. This method uses the power method to reduce the computation time compared with the conventional method. As a practical application, the harmonic retrieval problem is considered in the case of an input data sequence composed of N sinusoids in additive white noise. The effectiveness of the proposed method is confirmed. >

The authors describe speech segmentation and clustering algorithms based on speaker features, where speakers, the number of speakers, and speech context are unknown. Several problems are formulated and their solutions are proposed. As in the simpler case, when speech segmentations are known, the output probability clustering algorithm is proposed. In the case of unknown segmentation, an ergodic HMM (hidden Markov model)-based technique is applicable. Both cases are evaluated using simulated multispeaker dialogue speech data. >