The research for rational quadratic Bézier curve and its applications for generating conics and curve-fitting have been reported in some papers. But rational cubic Bézier curves, for the complexity of computation of the weight parameters and the difficulty of the shape control, have very rarely been applied up to the present. In this letter, we proposed a new method to generate a rational cubic Bézier curve. For a given point S (assuming the curve pass it) and a given value of the intermediate variable t in the point, we can compute the weight parameters of the rational cubic Bézier curve according to the relation of the control polygon and the given point, and can generate the curve. Then we explained the relation among shape of curve, given point S and intermediate varisble t. As the samples of using the method, we showed the generation of the gear-shape curve, symmetrical curve and spindle-shape curve, etc.. Finally, we discuss the application of this method for curve-fitting.

A precise method for determining AlGaAs/GaAs HBT large-signal circuit parameters is presented. In this method, the parameters are extracted from noise parameters and small-signal S-parameters measured under various bias conditions. The measured noise parameters are fitted to the calculated noise parameters derived from an approximation of Hawkins' equations applied to the macroscopic equivalent circuit. The small-signal S-parameters help to determine the large-signal circuit parameters. The derived large-signal parameters were used to design an HBT oscillator. The simulated results using these parameters were in good agreement with the fabricated device performance.

We indicate the existence of optimum expanded mode field diameters in thermally-diffused expanded core (TEC) fiber. The optimum ranges under our experimental conditions were from 14µm to 18µm for both 1.3µm-single-mode fiber and 1.55µm-dispersion-shifted fiber. By applying the TEC fiber fabricated in our experimental conditions to a multifiber connector, the connection loss can be reduced to less than 0.2dB without improving fiber and connector ferrule fabrication accuracy.

This paper describes the higher-order moment analysis of superposed Markov jumping processes. A superposed Markov jumping process is defined as a linear superposition of a finite number of piecewise constant real valued stochastic process whose value changes are associated with state transitions in an underlying descrete state continuous time Markov process. Some phenomena are modeled well by the process such as membrane current fluctuations observed at bio-membranes or load fluctuations in electrical power systems. Theoretical formula of the moment function of any order k is derived and the parameter estimation problem utilizing higher-order moment functions is discussed. A new method of estimating the kinetic parameters of membrane current fluctuations is proposed as a possible application.

This paper describes a new trial of dynamical parameter estimation for the actual room acoustic system, in a practical case when the input excitation is polluted by a background noise in contrast with the usual case when the output observation is polluted. The room acoustic system is first formulated as a discrete time model, by taking into consideration the original standpoint defining the system parameter and the existence of the background noise polluting the input excitation. Then, the recurrence estimation algorithm on a reverberation time of room is dynamically derived from Bayesian viewpoint (based on the statistical information of background noise and instantaneously observed data), which is applicable to the actual situation with the non-Gaussian type sound fluctuation, the non-linear observation, and the input background noise. Finally, the theoretical result is experimentally confirmed by applying it to the actual estimation problem of a reverberation time.

GaAs MESFETs with a p-buffer layer (or a buried p-layer) are important devices for high-speed GaAs ICs. To study what conditions are required as a good substrate for ICs, we have investigated, by two-dimensional simulation, small-signal parameters and drain-current transients of GaAs MESFETs with a p-buffer layer on the semi-insulating substrate. It is shown that the introduction of a p-buffer layer is effective to improve the transconductance and the cuttoff frequeycy. These parameters are not degrade even if the p-layer doping is increased and a neurtral p-region exists. It is also shown that drain-current drifts and hysteresis in I-V curves can occur in a case with a p-buffer layer, too. It is concluded that the introduction of a relatively highly-doped p-layer on a substrate with low acceptor and electron trap (EL2) densities is effective to realize the stable and high performance of GaAs MESFETs.

This paper describes the integration of a qualitative method and a quantitative method by Bottleneck Diagnosis/Improvement Expert Systems for Synchronized queueing network (BDES-S and BIES-S). On the basis of qualitative reasoning, BDES-S can carry out parameter tuning in order to diagnose and improve bottlenecks of synchronized queueing networks. BDES-S can produce several alternative qualitative improvement plans for one bottleneck server. BIES-S can produce quantitative improvement equations for each qualitative improvement plan. Our method using BDES-S and BIES-S can integrate both quantitative and qualitative methods for parameter tuning on complicated queueing synchronized networks.

The a-Si films deposited on quartz substrates were crystallized by lateral sweep annealing in steep temperature gradient using a gas burner. Random nucleation in amorphous region was effectively suppressed in the temperature gradient, so lateral solid phase epitaxial growth from crystallites generated at the initial stage of lateral sweep annealing spread over 100 µm. Their crystallographic orientations were mostly (100).

The two most important parameters in reactive ion etching process, ion bombardment energy and flux, were extracted through a simple RF waveform measurement at the excitation electrode in a conventional cathode-coupled plasma RIE system. By using the extracted plasma parameters, damage and contamination in Si substrates induced by reactive ion etching in a SiCl4 plasma were investigated. A very convenient map representation of ion energy and ion flux was introduced in understanding the etching process occurring in the RIE system.

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)).

The effects of changing system parameters on job scheduling policies are studied for load balancing of multi-class jobs in a distributed computer system that consists of heterogeneous host computers connected by a single-channel communications network. A job scheduling policy decides which host should process the arriving jobs. We consider two job scheduling policies. The one is the overall optimal policy whereby jobs are scheduled so as to minimize the overall mean job response time. Tantawi and Towsley obtained the algorithm that gives the solution of the policy in the single class job environment and Kim and Kameda extended it to the multiple job class environment. The other is the individually optimal policy whereby jobs are scheduled so that every job may feel that its own expected response time is minimized. We can consider three important system parameters in a distributed computer system: the communication time of the network, the processing capacity of each node, and the job arrival rate of each node. We examine the effects of these three parameters on the two load balancing policies by numerical experiment.

Very high resolution images with more than 2,000*2.000 pels will play a very important role in a wide variety of applications of future multimedia communications ranging from electronic publishing to broadcasting. To make communication of very high resolution images practicable, we need to develop image coding techniques that can compress very high resolution images efficiently. Taking the channel capacity limitation of the future communication into consideration, the requisite compression ratio will be estimated to be at least 1/10 to 1/20 for color signals. Among existing image coding techniques, the sub-band coding technique is one of the most suitable techniques. With its applications to high-fidelity compression of very high resolution images, one of the major problem is how to encode high frequency sub-band signals. High frequency sub-band signals are well modeled as having approximately memoryless probability distribution, and hence the best way to solve this problem is to improve the quantization of high frequency sub-band signals. From the standpoint stated above, the work herein first compares three different scalor quantization schemes and improved permutation codes, which the authors have previously developed extending the concept of permutation codes, from the aspect of quantization performance for a memoryless probability distribution that well approximates the real statistical properties of high frequency sub-band signals, and thus demonstrates that at low coding rates improved permutation codes outperform the other scalor quatization schemes and that its superiority decreases as its coding rate increases. Moreover, from the results stated above, the work herein, develops a rate-adaptive quantization technique where the number of bits assigned to each subblock is determined according to the signal variance within the subblock and the proper quantization scheme is chosen from among different types of quantization schemes according to the allocated number of bits, and applies it to the high-fidelity encoding of sub-band signals of very high resolution images to demonstrate its usefulness.

This paper describes a new approach towards the performance-driven layout for analog LSIs. Based on our approach, we developed an automatic performance-driven layout system LIBRA. The performance-driven layout has an advantage that numerical evaluations of performance requirements may exactly specify layout requirements so that a better layout result will be expected with regard to both the size and the performances. As the first step to the final goal, we only concern with the DC characteristics of analog circuits affected by the placement and routing. First of all, LIBRA performs the sensitivity analysis with respect to process parameters and wire parasitics, which are major causes for DC performance deviations of analog LSIs, so as to describe every perfomance deviation by its first order approximation. Based on the estimations of those performance deviations, LIBRA designs the placement of devices. The placement approach here is the simulated annealing method driven by their circuit performance specification. The routing of inter-cell wires is performed according to the priority of the larger total wire sensitivities in the net by the maze router. Then, the simple compaction eliminates the empty space as much as possible. After that, the power lines optimization is performed so as to minimize the ferformance deviations. Finally, an advantage of the performance improvement by our approach is demonstrated by showing a layout result of a practical bipolar circuit and its excellent performance evaluations.

This work describes a new analytical MOSFET model for analog circuit simulation based on the charge-sheet model. The current equation consists of diffusion and drift components, therefore Ids is a smooth function of the applied voltages. Since the original charge-sheet model is valid only for long-channel transistors, it has been further developed to describe quarter-micron MOSFETs by introducing the lateral electric field Ey into the theory. The new model includes these field contributions self-consistently, and describes the drain current of MOSFETs from long to quarter-micron channel lengths with a single model parameter set without discontinuities in derivatives of the drain current Ids. The mobility reduction due to Ey is described by an empirical equation with physical parameter values taken from literature. Only two fitting parameters, the impurity scattering and the surface roughness scattering in the mobility equation, are added to the physical parameters. The subdiffusion lengths are also taken as fitting parameters. Though the new model reduces the number of fitting parameters totally to four, it reproduces measured Ids excellently for MOSFETs with all channel lengths. The model has been included in the parameter extraction program JANUS, which extracts model parameters automatically. The algorithm for parameter extraction is summarized.

This paper investigates the performance of the line spectrum pair (LSP) frequency parameter representation for speech recognition. Transitional parameters of LSP frequencies are defined using first-order regression coefficients. The transitional and the instantaneous frequency parameters are linearly combined to generate a single feature vector used for recognition. The performance of the single vector is compared with that of the cepstral coefficients (CC) representation using a minimumdistance classifier in speaker-independent isolated word recognition experiments. In the speech recognition experiments, the transitional and the instantaneous coefficients are also combined in the distance domain. Also, inverse variance weighted Euclidean measures are defined using LSP frequencies to achieve Mel-scale-like warping and the new warped-frequencies are used in recognition experiments. The performance of the single feature vector defined with transitional and instantaneous LSP frequencies is found to be the best among the measures used in the experiments.