127 resultados para Generalized Lévy Process
em Indian Institute of Science - Bangalore - Índia
Resumo:
A generalized technique is proposed for modeling the effects of process variations on dynamic power by directly relating the variations in process parameters to variations in dynamic power of a digital circuit. The dynamic power of a 2-input NAND gate is characterized by mixed-mode simulations, to be used as a library element for 65mn gate length technology. The proposed methodology is demonstrated with a multiplier circuit built using the NAND gate library, by characterizing its dynamic power through Monte Carlo analysis. The statistical technique of Response. Surface Methodology (RSM) using Design of Experiments (DOE) and Least Squares Method (LSM), are employed to generate a "hybrid model" for gate power to account for simultaneous variations in multiple process parameters. We demonstrate that our hybrid model based statistical design approach results in considerable savings in the power budget of low power CMOS designs with an error of less than 1%, with significant reductions in uncertainty by atleast 6X on a normalized basis, against worst case design.
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Exact N-wave solutions for the generalized Burgers equation u(t) + u(n)u(x) + (j/2t + alpha) u + (beta + gamma/x) u(n+1) = delta/2u(xx),where j, alpha, beta, and gamma are nonnegative constants and n is a positive integer, are obtained. These solutions are asymptotic to the (linear) old-age solution for large time and extend the validity of the latter so as to cover the entire time regime starting where the originally sharp shock has become sufficiently thick and the viscous effects are felt in the entire N wave.
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Modeling and analysis of wave propagation in elastic solids undergoing damage and growth process are reported in this paper. Two types of diagnostic problems, (1) the propagation of waves in the presence of a slow growth process and (2) the propagation of waves in the presence of a fast growth process, are considered. The proposed model employs a slow and a fast time scale and a homogenization technique in the wavelength scale. A detailed analysis of wave dispersion is carried out. A spectral analysis reveals certain low-frequency bands, where the interaction between the wave and the growth process produces acoustic metamaterial-like behavior. Various practical issues in designing an efficient method of acousto-ultrasonic wave based diagnostics of the growth process are discussed. Diagnostics of isotropic damage in a ductile or quasi-brittle solid by using a micro-second pulsating signal is considered for computer simulations, which is to illustrate the practical application of the proposed modeling and analysis. The simulated results explain how an estimate of signal spreading can be effectively employed to detect the presence of a steady-state damage or the saturation of a process.
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The precipitation processes in dilute nitrogen alloys of titanium have been examined in detail by conventional transmission electron microscopy (CTEM) and high-resolution electron microscopy (HREM). The alloy Ti-2 at. pct N on quenching from its high-temperature beta phase field has been found to undergo early stages of decomposition. The supersaturated solid solution (alpha''-hcp) on decomposition gives rise to an intimately mixed, irresolvable product microstructure. The associated strong tweed contrast presents difficulties in understanding the characteristic features of the process. Therefore, HREM has been carried out with a view to getting a clear picture of the decomposition process. Studies on the quenched samples of the alloy suggest the formation of solute-rich zones of a few atom layers thick, randomly distributed throughout the matrix. On aging, these zones grow to a size beyond which the precipitate/matrix interfaces appear to become incoherent and the alpha' (tetragonal) product phase is seen distinctly. The structural details, the crystallography of the precipitation process, and the sequence of precipitation reaction in the system are illustrated.
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In this paper, we first recast the generalized symmetric eigenvalue problem, where the underlying matrix pencil consists of symmetric positive definite matrices, into an unconstrained minimization problem by constructing an appropriate cost function, We then extend it to the case of multiple eigenvectors using an inflation technique, Based on this asymptotic formulation, we derive a quasi-Newton-based adaptive algorithm for estimating the required generalized eigenvectors in the data case. The resulting algorithm is modular and parallel, and it is globally convergent with probability one, We also analyze the effect of inexact inflation on the convergence of this algorithm and that of inexact knowledge of one of the matrices (in the pencil) on the resulting eigenstructure. Simulation results demonstrate that the performance of this algorithm is almost identical to that of the rank-one updating algorithm of Karasalo. Further, the performance of the proposed algorithm has been found to remain stable even over 1 million updates without suffering from any error accumulation problems.
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There are essentially two different phenomenological models available to describe the interdiffusion process in binary systems in the olid state. The first of these, which is used more frequently, is based on the theory of flux partitioning. The second model, developed much more recently, uses the theory of dissociation and reaction. Although the theory of flux partitioning has been widely used, we found that this theory does not account for the mobility of both species and therefore is not suitable for use in most interdiffusion systems. We have first modified this theory to take into account the mobility of both species and then further extended it to develop relations or the integrated diffusion coefficient and the ratio of diffusivities of the species. The versatility of these two different models is examined in the Co-Si system with respect to different end-member compositions. From our analysis, we found that the applicability of the theory of flux partitioning is rather limited but the theory of dissociation and reaction can be used in any binary system.
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A method is presented for obtaining useful closed form solution of a system of generalized Abel integral equations by using the ideas of fractional integral operators and their applications. This system appears in solving certain mixed boundary value problems arising in the classical theory of elasticity.
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A method has been developed for the removal of chromium using ferrous sulphide generated in situ. The effects of experimental parameters such as pH, reagent dosages, interference from cations and chelating agents have been investigated. Under optimum conditions, removal efficiencies of 99 and 97% for synthetic and industrial samples have been obtained. The method offers all the advantages of sulphide precipitation process and can be adopted easily for industrial effluents.
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A numerical model of the entire casting process starting from the mould filling stage to complete solidification is presented. The model takes into consideration any phase change taking place during the filling process. A volume of fluid method is used for tracking the metal–air interface during filling and an enthalpy based macro-scale solidification model is used for the phase change process. The model is demonstrated for the case of filling and solidification of Pb–15 wt%Sn alloy in a side-cooled two-dimensional rectangular cavity, and the resulting evolution of a mushy region and macrosegregation are studied. The effects of process parameters related to filling, namely degree of melt superheat and filling velocity on macrosegregation in the cavity, are also investigated. Results show significant differences in the progress of the mushy zone and macrosegregation pattern between this analysis and conventional analysis without the filling effect.
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Boron carbide is produced in a heat resistance furnace using boric oxide and petroleum coke as the raw materials. The product yield is very low. Heat transfer plays an important role in the formation of boron carbide. Temperature at the core reaches up to 2600 K. No experimental study is available in the open literature for this high temperature process particularly in terms of temperature measurement and heat transfer. Therefore, a laboratory scale hot model of the process has been setup to measure the temperatures in harsh conditions at different locations in the furnace using various temperature measurement devices such as pyrometer and various types of thermocouple. Particular attention was paid towards the accuracy and reliability of the measured data. The recorded data were analysed to understand the heat transfer process inside the reactor and the effect of it on the formation of boron carbide.
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This paper describes the design and implementation of a high-level query language called Generalized Query-By-Rule (GQBR) which supports retrieval, insertion, deletion and update operations. This language, based on the formalism of database logic, enables the users to access each database in a distributed heterogeneous environment, without having to learn all the different data manipulation languages. The compiler has been implemented on a DEC 1090 system in Pascal.
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Abstract is not available.
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Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.
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A generalized pulse pair has been suggested in which the longitudinal spin order is retained and the transverse components cancelled by random variation of the interval between pulses, in successive applications of the two-dimensional NMR algorithm. This method leads to pure phases and has been exploited to provide a simpler scheme for two-spin filtering and for pure phase spectroscopy in multiple-quantum-filtered two-dimensional NMR experiments.
Resumo:
Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.