We studied various types of 2D and 3D Si-based photonic crystal structures that are promising for future photonic integrated circuit application. With regard to 2D SOI photonic crystal slabs, we confirmed the formation of a wide photonic bandgap at optical communication wavelengths, and used structural tuning to realize efficient single-mode line-defect waveguides operating within the bandgap. As regards 3D photonic crystals, we used a combination of lithography and the autocloning deposition method to realize complicated 3D structures. We used this strategy to fabricate 3D full-gap photonic crystals and 3D/2D hybrid photonic crystals.

Synchrotron radiation (SR) irradiation of amorphous SiO2 (a-SiO2) induces continuous removal of the SiO2 film without the use of etching gas. The dependence of the photostimulated evaporation rate on substrate temperature and SR intensity was measured and the reaction mechanism is discussed in detail separately for surface and bulk. Using the high material selectivity of the Sr-stimulated evaporation, a sefl-aligned process to fabricate a 0.6 µm line-and-space pattern is presented. Si surface cleaning is demonstrated as an example of application of this reaction to thin native oxide film grown by wet pretreatment. Si(100)-21 and Si(111)-77 structures were observed by reflection high energy electron diffraction (RHEED) at temperatures as low as 650. The difference between a-SiO2 and native oxide on the evaporation rate is higlighted. Epitaxial Si growth using disilane (Si2H6) gas occurs selectively in the SR-irradiated region on a Si(100) surface. Using SR irradiation in an ultrahigh vacuum, followed by residual oxide reduction by disilane, is proposed as an effective cleaning method.

We carried out degradation analysis of a blue phosphorescent organic light emitting diode by both impedance spectroscopy and transient electroluminescence (EL) spectroscopy. The number of semicircles observed in the Cole-Cole plot of the modulus became three to two after the device was operated for 567 hours. Considering the effective layer thickness of the initial and degraded devices did not change by degradation and combining the analysis of the Bode-plot of the imaginary part of the modulus, the relaxation times of emission layer and hole-blocking with electron transport layers changed to nearly the same value by the increase of the resistance of emission layer. Decay time of transient EL of the initial device was coincident with that of the degraded one. These phenomena suggest that no phosphorescence quenching sites are generated in the degraded device, but the number of the emission sites decrease by degradation.

A silicon (Si) wire waveguiding system fabricated on silicon-on-insulator (SOI) substrates is one of the most promising platforms for highly-integrated, ultra-small optical circuits, or microphotonics devices. The cross-section of the waveguide's core is about 300-nm-square, and the minimum bending radius are a few micrometers. Recently, crucial problems involving propagation losses and in coupling with external circuits have been resolved. Functional devices using silicon wire waveguides are now being tested. In this paper, we describe our recent progress and future prospects on the microphotonics devices based on the silicon-wire waveguiding system.

This paper presents a hardware architecture design methodology for hidden markov model based recognition systems. With the aim of realizing more advanced and user-friendly systems, an effective architecture has been studied not only for decoding, but also learning to make it possible for the system to adapt itself to the user. Considering real-time decoding and the efficient learning procedures, a bi-directional ring array processor is proposed, that can handle various kinds of data and perform a large number of computations efficiently using parallel processing. With the array architecture, HMM sub-algorithms, the forward-backward and Baum-Welch algorithms for learning and the Viterbi algorithm for decoding, can be performed in a highly parallel manner. The indispensable HMM implementation techniques of scaling, smoothing, and estimation for multiple observations can be also carried out in the array without disturbing the regularity of parallel processing. Based on the array processor, we propose the configuration of a system that can realize all HMM processes including vector quantization. This paper also describes that a high PE utilization efficiency of about 70% to 90% can be achieved for a practical left-to-right type HMMs.

This paper describes how to effectively use discriminative training based on Minimum Classification Error (MCE) criterion for a small amount of data in order to attain the highest level of recognition performance. This method is a combination of MCE training and Vector-Field-Smoothed Bayesian learning called MAP/VFS, which combines maximum a posteriori (MAP) estimation with Vector Field Smoothing (VFS). In the proposed method, MAP/VFS can significantly enhance MCE training in the robustness of acoustic modeling. In model training, MCE training is performed using the MAP/VFS-trained model as an initial model. The same data are used in both trainings. For speaker adaptation using several dozen training words, the proposed method has been experimentally proven to be very effective. For 50-word training data, recognition errors are drastically reduced by 47% compared with 16.5% when using only MCE. This high rate, in which 39% is due to MAP, an additional 4% is due to VFS, and a further improvement of 4% is due to MCE, can be attained by enhancing MCE training capability by MAP/VFS.