One stochastic process and its application to multiple access insupercritical region

A discrete-argument stochastic process is presented. The process is a generalization of the Cinlar (1975) semiregenerative process and process η(t) given in Tsybakov (1993). For this process, the theorem, which is similar to the Smith regenerative process theorem, is given. We use this theorem to find the transmission rate and mean packet delay for stack and part-and-try random multiple access algorithms in their supercritical regions. For the part-and-try algorithm, the results are new. For the stack algorithm, we give a new method of finding the rate and delay     

Continuous n-tuple classifier and its application to facerecognition

The author describes the continuous n-tuple classifier: a new type of n-tuple classifier that is ideally suited to problems where the input is continuous or multi-level rather than binary. Results on a widely used face database show the continuous n-tuple classifier to be as accurate as any method reported in literature, while having the advantages of speed and simplicity over other methods     

Continuous n-tuple classifier and its application to real-time facerecognition

The continuous n-tuple classifier was proposed by the author as a new type of n-tuple classifier that is ideally suited to problems where the input is continuous or multi-level rather than binary. Results on a widely used face database show the continuous n-tuple classifier to be as accurate as any method reported in the literature, while having the advantages of speed and simplicity over other methods. The author summarises the previous work, provides new insight into how the system works and discusses its applicability to real-time face recognition     

The branching nonhomogeneous Poisson process and its application to a replacement model

In studying and analysing the failure patterns of complex system, plausible stochastic models are needed to represent the sequence of events. A simple and frequently used model is derived by the assumption that the times-between-failures of a system are exponentially distributed and independent. Experience has shown, however, that successive times-between-failures are not exponentially distributed and not independent.These deviations are due to imperfect search of failed components. We constitute a plausible stochastic process which describes the sequence of events, and obtain the interval reliability and the expected number of failures.As an application of these results, we deal with the replacement model where a system undergoes minimal repair before time T and is replaced at time T. We discuss an optimum policy minimizing the total expected cost per unit time.     

A model-based approach for process design and its application tothe titanium salicide process

Process technology development constitutes a significant cost in manufacturing integrated circuits. In this paper, we present a model-based approach for developing new process technology rapidly and inexpensively, using the salicide process to demonstrate the concepts. This approach is applied to evaluate performance tradeoffs, to develop insight into the underlying process physics, to quantify the impact of the salicide process on the device and circuit performance, and to estimate the process variability. The key idea of this approach is to group a sequence of process steps into a process module, and build simple and accurate process models for the module. The paper also illustrates the use of this model-based approach in synthesizing optimal processes rapidly based on requirements, contributing to the reduction of technology development cost and cycle time     

Derivation of a nonlinear variance equation and its application toSOI technology

An analytic nonlinear equation for variance was derived along with a method based on response surface mapping techniques to calculate the variance using the proposed equation. The technique was applied to the threshold voltage of a 0.1-μm silicon-on-insulator MOS device, and the variance value obtained was verified using Monte Carlo simulation. The threshold voltage dependence upon active-layer thickness was found to be highly nonlinear due to the device's going from the fully depleted to the partially depleted regime. Analysis of the variance showed that the effect of the nonlinear terms (18.7%) is more important than the effect of the mixed term (-0.7%) and almost as important as the contribution of the second most dominant input-process parameter (23.6%). This illustrates the importance of the proposed nonlinear equation     

Ordering of spectral factors and its application

In connection with the solution of matrix Wiener-Hopf equations, the need for the correct ordering of spectral factors is emphasised. Modifications to the method of augmented factors are presented to accommodate the reverse-ordering of spectral factors.     

The edge process model and its application to information-hiding capacity analysis

In this paper, the problem of capacity analysis of data-hiding techniques in a game information-theoretic framework is considered. Capacity is determined by the stochastic model of the host image, by the distortion constraints, and by the side information about the watermarking channel state available at the encoder and at the decoder. The importance of the proper modeling of image statistics is emphasized, and for this purpose, a novel stochastic nonstationary image model is proposed that is based on geometrical priors, the so-called edge process model. Being mathematically simple and tractable, the edge process model outperforms the estimation-quantization (EQ) and spike process models in reference applications such as denoising. Finally, this model allows us to obtain a realistic estimate of maximal embedding rates, and in particular, it is shown that the expected capacity limit of real images is significantly lower than previously reported.     

The use of an adaptive threshold element to design a linear optimal pattern classifier

This paper develops a relationship between two traditional statistical methods of pattern classifier design, and an adaption technique involving minimization of the mean-square error in the output of a linear threshold device. It is shown that the two-category classifier derived by least-mean-square-error adaption using an equal number of sample patterns from each category is equivalent to the optimal statistical classifier if the patterns are multivariate Gaussian random variables having the same covariance matrix for both pattern categories. It is also shown that the classifier is always equivalent to the classifier derived by R. A. Fisher. A simple modification of the least-mean-square-error adaption procedure enables the adaptive structure to converge to a nearly-optimal classifier, even though the numbers of sample patterns are not equal for the two categories. The use of minimization of mean-square error as a technique for designing classifiers has the added advantage that it leads to the optimal classifier for patterns even when the covariance matrix is singular.     

The Bayesian hierarchical classifier (BHC) and its application to short vegetation using multifrequency polarimetric SAR

Given an image of a scene comprised of a number of distinct terrain classes, the optimum Bayesian classifier (OBC) provides the highest possible classification accuracy of the imaged scene, provided we have a priori knowledge of the probability density function (pdf) of the sensor's output for each terrain class. If the imaging sensor consists of multiple channels, application of OBC requires knowledge of the joint pdf of the observations made by all the channels. In practice, the volume of data needed in order to generate an accurate multidimensional pdf far exceeds the size of available datasets. The data-size requirement may be relaxed by assuming the pdfs to be Gaussian in form, but such an assumption leads to suboptimum classification performance. This paper addresses the data size issue by (1) taking advantage of the maximum-entropy density estimation (MEDE) technique introduced in a companion paper and (2) using marginal pdfs in a hierarchical approach. Using multidate synthetic aperture radar observations, it was shown that the Bayesian hierarchical classifier introduced in this paper can classify short vegetation classes with an accuracy of 93%, without retraining, compared with an accuracy of 84% for the maximum-likelihood estimator (with Gaussian assumption) and only 74% with ISODATA.     

整车电气故障诊断的流程设计及应用

基于提高某主机厂在开发设计阶段时的故障诊断软件的使用效率,本文针对该诊断软件进行了人机接口控制设计,可将多个诊断命令的发送操作通过一个按键实现,并通过实际操作验证,该人机接口控制设计可减少软件操作次数,工作效果稳定,可提高工作效率。然后本文结合电气故障排查的工作经验,设计了整车电气故障诊断排查的流程和方法,并按照诊断流程和方法进行实际工作验证,多次工作验证表明,本流程可较快定位电气故障。     

On surface EMG spectral characterization and its application to diagnostic classification

Surface EMG was recorded from the biceps with fixed muscle length at S0 percent maximal voluntary contraction. The signal bandpass was 10-230 Hz where most of the surface EMG energy is located. The signal sampled at 500 Hz was found to have a changing spectrum. Stationary segments of 500 ms were subject to linear prediction mathematics to model the system.     

Influence of spectral characteristics of a process on its absolute maximum distribution

The estimate of the initial moments in the distribution of an absolute maximum of a stationary Gaussian process at the output of a low pass recursive digital filter with the specified parameters is determined by modeling in the MATLAB and Excel environments. The correspondence of the obtained result to the theoretical conclusions on the independence of the distribution characteristics of the absolute maximum distribution and of the behavior of the correlation function of the process outside the zero value of its argument is proven.     

电气工程自动化及其节能设计的应用探究

随着社会的不断发展,物质生活得到大幅度的提高,整个社会对电气工程自动化技术的关注程度得以提高。同时,也是为了适应国家的能源发展计划,满足节能减排的实际需要。本文主要分析了当前电气工程自动化发展的状态,介绍了存在的不足,有针对性地提出了解决的对策,充分表达了对节能技术的重视,有助于为电气自动化节能技术在实际中的运用。     

RF integrated inductor modeling and its application to optimization-based design

In this paper an optimization-based approach for the design of RF integrated inductors is addressed. For the characterisation of the inductor behaviour the double ??-model is used. The use of this model is twofold. On one hand it enables the generation of the inductor characterisation in a few seconds. On the other hand its integration into the optimization procedure is straightforward. For the evaluation of the model element values analytical expressions based on technology parameters as well as on the device geometric characteristics are used. The use of a technology-based methodology for the evaluation of the model parameters grants the adaptability of the model to any technology. The inductor analytical characterization is integrated into an optimization-based tool for the automatic design of RF integrated inductors. This tool uses a modified genetic algorithm (MGA) optimization procedure, which has proved its validation in previous work. Due to the design parameter constraints nature as well as the topology constraints, discrete variables optimization techniques are used. The accuracy of the results is checked against a non-commercial software.     

电气工程自动化及其节能设计的应用探究

随着社会的不断发展,物质生活得到大幅度的提高,整个社会对电气工程自动化技术的关注程度得以提高。同时,也是为了适应国家的能源发展计划,满足节能减排的实际需要。本文主要分析了当前电气工程自动化发展的状态,介绍了存在的不足,有针对性地提出了解决的对策,充分表达了对节能技术的重视,有助于为电气自动化节能技术在实际中的运用。     

Fractal dimension estimation via spectral distribution function and its application to physiological signals

Rhythmic signals from physiological systems usually have memory and long-term correlation. They can be modeled as fractional Brownian motion or fractional Gaussian noise depending on if the signals are derived from cumulative effects of nerves and muscles. That is, they can be treated as signals with fractional dimension, and the value of its fractal dimension can be used to characterize the intensity of physiological signals. In this communication, a novel method of dimension estimation based on the calculation of spectral distribution function of discrete-time fractional Gaussian noise using Legendre polynomials as basis set is proposed. The effectiveness of this proposed method is demonstrated in the dynamic behavior of detrusor of the bladder and external urethral sphincter during micturition.     

Generalized scaling theory and its application to a ¼ micrometer MOSFET design

In this paper we present a generalized scaling theory which allows for an independent scaling of the FET physical dimensions and applied voltages, while still maintaining constant the shape of the electric-field pattern. Thus two-dimensional effects are kept under control even though the intensity of the field is allowed to increase. The resulting design flexibility allows the design of FET's with quarter-micrometer channel length to be made, for either room temperature or liquid-nitrogen temperature. The physical limitations of the scaling theory are then investigated in detail, leading to the conclusion that the limiting FET performances are not reached at the 0.25-µm channel length. Further improvements are possible in the future, provided certain technology breakthroughs are achieved.     

The application of spectral estimation methods to bearing estimation problems

The equivalence between the problem of determining the bearing of a radiating source with an array of sensors and the problem of estimating the spectrum of a signal is demonstrated. Modern spectral estimation algorithms are derived within the context of array processing using an algebraic approach. Emphasis is placed on the problem of determining the bearing of a sound source with an array. Special issues encountered in applying these estimates are discussed.     

Dynamic noise model and its application to high speed circuit design

A dynamic noise model is developed and applied to analyze the noise immunities of precharge-evaluate circuits. With cross-talk being the main source of noise injection in the circuit, a simple metric represented as voltage-time product can be used to quantify the dynamic noise-margin. This is verified through HSPICE simulation on DOMINO gates. Based on this dynamic noise model, a tool is developed and applied to find the static and dynamic noise-margins at various points in the circuit with the effects of charge share and power/ground bounce taken into account. Obtained noise-margins are translated into maximum allowable coupling capacitances between the nodes for different types of precharge-evaluate logic circuits. The results show the difference in dynamic noise immunities in different logic families. Accurate estimates of dynamic noise-margins and coupling capacitance bounds will help design robust CMOS circuits.