Tremendous progress has been made in magnetic data storage by applying theoretical considerations to technologies accumulated empirically through a great deal of research and development. In Japan, the recording demagnetization phenomenon was eagerly analyzed by many researchers because it was a serious problem in analogue signal recording such as video tape recording using a relatively thick magnetic recording medium. Consequently, perpendicular magnetic recording was proposed as a method for extremely high-bit-density recording. This paper describes the theoretical background which has resulted in the idea of perpendicular magnetic recording. Furthermore, the possibility of magnetic recording is discussed on the basis of the results obtained theoretically by magnetic recording simulators. Magnetic storage has the potential for extremely high-bit-density recording exceeding 1 Tb/cm2. We propose the idea of 'spinic data storage' in which binary digital data could be stored into each ferromagnetic single-domain columnar particle when the perpendicular magnetizing method is used.

We discuss how to determine automatically the number of mixture components in continuous mixture density HMMs (CHMMs). A notable trend has been the use of CHMMs in recent years. One of the major problems with a CHMM is how to determine its structure, that is, how many mixture components and states it has and its optimal topology. The number of mixture components has been determined heuristically so far. To solve this problem, we first investigate the influence of the number of mixture components on model parameters and the output log likelihood value. As a result, in contrast to the mixture number uniformity" which is applied in conventional approaches to determine the number of mixture components, we propose the principle of distribution size uniformity". An algorithm is introduced for automatically determining the number of mixture components. The performance of this algorithm is shown through recognition experiments involving all Japanese phonemes. Two types of experiments are carried out. One assumes that the number of mixture components for each state is the same within a phonetic model but may vary between states belonging to different phonemes. The other assumes that each state has a variable number of mixture components. These two experiments give better results than the conventional method.

A high-speed high-density self-aligned pnp technology for complementary bipolar ULSIs has been developed to achieve high-speed and low-power performance simultaneously. It is fully compatible with the npn process. A low sheet-resistance p+ buried layer and a low sheet-resistance extrinsic n+ polysilicon layer with U-grooved isolation enable the transistor size to be scaled down to about 20 µm2. Current gain of 85 with 4-V collector-emitter breakdown voltage was obtained without any leakage current arising from emitter-base forward tunneling or recombination, which indicates no extrinsic base encroachment problem. A shallow emitter junction depth of 45 nm and narrow base width of 30 nm, obtained by utilizing an optimized retrograded p-well, an arsenic-implanted intrinsic base, and emitter diffusion from BF2-implanted polysilicon, improve the maximum cutoff frequency to 35 GHz. The power dissipation of the pnp pull-down complementary emitter-follower ECL circuit with load capacitances is calculated to be reduced to 20-40% of a conventional ECL circuit.

An excitation signal for a synthesis filter plays an important role in producing high quality speech at a low bit rate. This paper presents a new efficient excitation model, Adaptive Density Pulse (ADP) , for low bit-rate speech coding. This ADP is a pulse train whose density (spacing interval) is constant within a subframe but can be varied subframe by subframe. First, the ADP excitation signal is defined. A procedure for finding the optimal ADP excitation is presented. Some results on investigating the effects of the ADP parameters on the synthesized speech quality are discussed. ADP excitation is introduced to the CELP (Code Excited Linear Prediction) coding method to improve speech quality at bit rates around 4 kbps. A CELP coder with an ADP (ADP-CELP) is described. ADP excitation makes it possible for the CELP coder to follow transient portions of speech signals. Also ADP excitation can reduce computational complexity in selecting the best excitation from a codebook, which has been the primary drawback of CELP. The number of multiplications can be reduced to the order of 1/D2 by utilizing the sparseness of ADP excitation, where D is the pulse interval. The authors evaluated the speech quality of a 4 kbps ADP-CELP coder by computer simulation. ADP excitation improved the performance of conventional CELP in segmental SNR.

Plating is applied to protect contact surfaces of contact devices such as switch, relay and connector from contaminations of oxidization and sulfuration etc. Furthermore it is known that the contact resistance can be reduced when there exist plated layers on the contact surfaces which have enough thickness and low resistivity compared with substratum materials. In this paper, contact resistance between plated conductors are calculated using three dimensional finite element method. Similariry, current density distribution in a contact spot with various resistivity of plated layers are shown and relative conductance depends on the contact area fraction with thickness of plated layers are presented.

The electric or electronic circuits have many contact devices such as relay and switch. The contact between two nominally conducting flat surface has a lot of micro contact spots. The constriction resistance of the contact is known to determine the sum of the parallel resistance of the micro contacts and the interaction of them. The constriction resistance of two circular conducting spots was approximately formulated by Greenwood. This formulation shows that the interacted resistance of two circular spots is in inverse proportion to the distance between two conducting spots. It was known that this effect is introduced by the interaction between two conducting spots. However, the condition of interaction in the spots is not clear. Calculating the current density distribution in the spots is important to clarify the condition of interaction. The numerical analysis is very suitable to calculate the current density in the spots. In the fundamental case of the computation of the current density the boundary element method (BEM) is more efficient and accurate than that of the finite element method (FEM) because the boundary condition at the infinite is naturally satisfied and is not required a great number of the element in a wide space. In this paper the current density in the square spots is computed by the BEM. As the distance between two conducting spots becomes small, the current density in the two spots decreases. It becomes clear that the constriction resistance of conducting spots is increased by this effect. The decrease of current density by interaction is not uniformly, that at the near location to the opposite spot is larger than that at the far location in the same spot. In this paper the constriction resistance of two conducting spots is also considered. It was known that the constriction resistance of one conducting spot is not influenced by the form of spot very much. However, that of two conducting spots is not clear. The constriction resistance of two square spots is also computed by the BEM. The computed values of the constriction resistance of two square spots are compared with that of two circular spots by Greenwood's formulation and other results. As the result, it is clear that they have the considerable discrepancy. However, the trend of the variations is almost agree each other.

Multilevel RLL (Runlength Limited) sequences are analyzed. Their noiseless capacity and lower bounds on the channel capacity in the presence of additive white Gaussian noise are given. Moreover, the analytical power spectra formulae for those sequences which generalize the previously derived one for binary sequences are newly derived. We conclude from the analysis of the power spectra that multilevel RLL sequences are attractive from the point of view that they increase information rate while keeping low DC-content and self-clocking capability of binary RLL sequences.

A specific signal in most of actual environmental systems fluctuates complicatedly in a non-Gaussian distribution form, owing to various kinds of factors. The nonlinearity of the system makes it more difficult to evaluate the objective system from the viewpoint of internal physical mechanism. Furthermore, it is very often that the reliable observation value can be obtained only within a definite domain of fluctuating amplitude, because many of measuring equipment have their proper dynamic range and the original random wave form is unreliable at the end of amplitude fluctuation. It becomes very important to establish a new signal processing or an evaluation method applicable to such an actually complicated system even from a functional viewpoint. This paper describes a new trial for the signal processing along the same line of the extended regression analysis based on the Bayes' theorem. This method enables us to estimate the response probability property of a complicated system in an actual situation, when observation values of the output response are saturated due to the dynamic range of measuring equipment. This method utilizes the series expansion form of the Bayes' theorem, which is applicable to the non-Gaussian property of the fluctuations and various kinds of correlation information between the input and output fluctuations. The proposed method is newly derived especially by paying our attention to the statistical information of the input-output data without the saturation operation instead of that on the resultantly saturated observation, differing from the well-known regression analysis and its improvement. Then, the output probability distribution for another kind of input is predicted by using the estimated regression relationship. Finally, the effectiveness of the proposed method is experimentally confirmed too by applying it to the actual data observed for indoor and outdoor sound environments.

Checkpointing is one of the most powerful tools to operate a computer system with high reliability. We should execute the optimal checkpointing in some sense. This note shows the optimal checkpoint sequence minimizing the expected loss, Numerical examples are shown for illustration.

This paper presents a linear time optimal algorithm to a channel pin assignment problem for hierarchical building-block layout design. The channel pin assignment problem is to determine positions of the pins of nets on the top and the bottom sides of a channel, which are partitioned into several intervals, and the pins are permutable within their associated intervals. The channel pin assignment problem has been shown NP-hard in general. We present a linear time optimal algorithm for an important special case of the problem, in which there is at most one pin of a net within each interval in the channel. The proposed algorithm is optimal in a sense that it can minimize both the channel density and the total wire length of the channel. We also disscuss how to apply our algorithm to the pin assignment in the L-shaped and staircase channels. Experimental results indicate that substantial reduction in both channel density and estimated total wire length can be obtained by permuting pins in each interval. Combining the proposed algorithm with a conventional channel router, results of channel routing also achieve large amount of reduction of the number of tracks, total wire length, and the number of vias.

Nojima and Fujita have found a universal relation, irrespective of temperatures T, between the reduced field hH/Hir(T) and the reduced quantity of magnetization hysteresis mΔM (T, H)/ΔM (T, H0), where Hir is the irreversibility field and ΔM(T, H) is the hysteresis of magnetization for YBa2Cu3Ox and Bi2Sr2CaCu2Ox films. We could explain this universal relation based on a scaling theory in a three-dimensional superconducting vortex-glass phase. The exponent ν derived by this relation coincides with that obtained by nonlinear I-V characteristics for YBa2Cu3Ox films.

The concentration of the electric field at the edge of the electrode has been simulated in several types of flat DRAM cell capacitors with high permittivity dielectrics. The results indicated that the permittivity of the material surrounding the edge of the electrode as well as the geometrical structure affected the concentration of the electric field. The electric field strength was minimized and most evenly distributed by utilizing the structure in which the sidewall of the capacitor dielectric was terminated at the edge of the electrode by a low-dielectric constant insulator. High-precision fabrication of the capacitor's profile is required for the minimization and uniformity of the electric field.

The characteristics of an optical functional integrated circuit and its applications are discussed. This circuit is based upon a Mach-Zehnder interferometer type waveguide device employing thermo-optic effect. This circuit is compact, cost-effective and practical. One proposed application is an optical loopback circuit to test both OCU loop 1 and DSU loop C. This optical loopback circuit with an attenuator and space switches is formed on a common silicon substrate, and using this circuit both loopback and line tests are independently available at the same access point. The other is an optical selector. This optical selector with WDM-MUX/DMUX and space switches is formed on a common silicon substrate, and using this selector, wavelength selection from medium density WDM (MDWDM) signal can be performed. Each MDWDM signal carries both AM and FM-FDM video signals modulated by Subcarrier Multiplexing (SCM) techniques. This selector can be wired in point-to-multipoint configurations to home video appliances.

This paper proposes a model for learning non-parametric densities using finite-dimensional parametric densities by applying Yamanishi's stochastic analogue of Valiant's probably approximately correct learning model to density estimation. The goal of our learning model is to find, with high probability, a good parametric approximation of the non-parametric target density with sample size and computation time polynomial in parameters of interest. We use a learning algorithm based on the minimum description length (MDL) principle and derive a new general upper bound on the rate of convergence of the MDL estimator to a true non-parametric density. On the basis of this result, we demonstrate polynomial-sample-size learnability of classes of non-parametric densities (defined under some smoothness conditions) in terms of exponential families with polynomial bases, and we prove that under some appropriate conditions, the sample complexity of learning them is bounded as O((1/ε)(2r1)/2r1n(2r1)/2r(1/ε)(1/ε)1n(1/δ) for a smoothness parameter r (a positive integer), where ε and δ are respectively accuracy and confidence parameters. Futher, we demonstrate polynomial-time learnability of classes of non-parametric densities (defined under some smoothness conditions) in terms of histogram densities with equal-length cells, and we prove that under some appropriate condition, the sample complexity of learning them is bounded as O((1/ε)3/21n3/2(1/ε)(1/ε)1n(1/δ)).