An efficient bi-objective optimization framework for statistical chip-level yield analysis under parameter variations

With shrinking technology,the increase in variability of process,voltage,and temperature(PVT) parameters significantly impacts the yield analysis and optimization for chip designs.Previous yield estimation algorithms have been limited to predicting either timing or power yield.However,neglecting the correlation between power and delay will result in significant yield loss.Most of these approaches also suffer from high computational complexity and long runtime.We suggest a novel bi-objective optimization framework based on Chebyshev affine arithmetic(CAA) and the adaptive weighted sum(AWS) method.Both power and timing yield are set as objective functions in this framework.The two objectives are optimized simultaneously to maintain the correlation between them.The proposed method first predicts the guaranteed probability bounds for leakage and delay distributions under the assumption of arbitrary correlations.Then a power-delay bi-objective optimization model is formulated by computation of cumulative distribution function(CDF) bounds.Finally,the AWS method is applied for power-delay optimization to generate a well-distributed set of Pareto-optimal solutions.Experimental results on ISCAS benchmark circuits show that the proposed bi-objective framework is capable of providing sufficient trade-off information between power and timing yield.

The method of variation on parameters for integration of a generalized Birkhoffian system

This paper focuses on studying the integration method of a generalized Birkhoffian system.The method of variation on parameters for the dynamical equations of a generalized Birkhoffian system is presented.The procedure for solving the problem can be divided into two steps：the first step,a system of auxiliary equations is constructed and its general solution is given;the second step,the parameters are varied,and the solution of the problem is obtained by using the properties of generalized canonical transformation.The method of variation on parameters for the generalized Birkhoffian system is of universal significance,and we take a nonholonomic system and a nonconservative system as examples to illustrate the application of the results of this paper.

Scintrex CG5 used for superconducting gravimeter calibration

The scale factor accuracy of superconducting gravimeters （SG） can be largely improved by a high repetition rate of calibration experiments. At stations where the availability of absolute gravimeters is limited, carefully calibrated spring gravimeters can be used for providing the reference signal assuming the irregular drift is properly adjusted. The temporal stability of the SG scale factor is assessable by comparing the temporal variations of M2 tidal parameters observed at neighboring SG sites or from synthetic tide models. Combining these methods reduces the SG scale factor error to a few 0.1%0. The paper addresses the particular procedure required for evaluating the calibration experiments based on spring gravimeters and presents results obtained at Conrad observatory （Austria）. Comparing the M2 amplitude factor modulation helped to reveal a SG scale factor offset of about 0.2%0 due to re-installation.

Artificial Sun synchronous frozen orbit control scheme design based on J_2 perturbation

Sun synchronous orbit and frozen orbit formed due to J 2 perturbation have very strict constraints on orbital parameters,which have restricted the application a lot.In this paper,several control strategies were illustrated to realize Sun synchronous frozen orbit with arbitrary orbital elements using continuous low-thrust.Firstly,according to mean element method,the averaged rate of change of the orbital elements,originating from disturbing constant accelerations over one orbital period,was derived from Gauss＇ variation of parameters equations.Then,we proposed that binormal acceleration could be used to realize Sun synchronous orbit,and radial or transverse acceleration could be adopted to eliminate the rotation of the argument of the perigee.Finally,amending methods on the control strategies mentioned above were presented to eliminate the residual secular growth.Simulation results showed that the control strategies illustrated in this paper could realize Sun synchronous frozen orbit with arbitrary orbital elements,and can save much more energy than the schemes presented in previous studies,and have no side effect on other orbital parameters＇ secular motion.

BIFURCATIONS AND CHAOS CONTROL IN TCP-RED SYSTEM

Objective Analyzing the nonlinear dynamics of the TCP-RED congestion control system is of great importance. This study will help investigate the loss of stability in Internet and design a proper method for controlling bifurcation and chaos in such system. Methods Based on bifurcation diagram, the effect of parameter on system performance is discussed. By using the state feedback and parameter variation strategy, a simple real time control method is proposed to modify the existing RED scheme. Results With our control method, the parametric sensitivity of RED mechanism is attenuated. Moreover, a sufficient condition on the robust stability of the system is also derived to adjust the parameters in TCP-RED system. Conclusion The proposed method has the advantages of simple implementation and unnecessary knowledge of the exact system.

State-of-Charge Estimation of Lithium-Ion Battery for Electric Vehicles Using Deep Neural Network

It is critical to have precise data about Lithium-ion batteries,such as the State-of-Charge(SoC),to maintain a safe and consistent functioning of battery packs in energy storage systems of electric vehicles.Numerous strategies for estimating battery SoC,such as by including the coulomb counting and Kalman filter,have been established.As a result of the differences in parameter values between each cell,when these methods are applied to highcapacity battery packs,it has difficulties sustaining the prediction accuracy of overall cells.As a result of aging,the variation in the parameters of each cell is higher as more time is spent in operation.It is suggested in this study to establish an SoC estimate model for a Lithium-ion battery by employing an enhanced Deep Neural Network(DNN)approach.This is because the proposed DNN has a substantial hidden layer,which can accurately predict the SoC of an unknown driving cycle during training,making it ideal for SoC estimation.To evaluate the nonlinearities between voltage and current at various SoCs and temperatures,the proposed DNN is applied.Using current and voltage data measured at various temperatures throughout discharge/charge cycles is necessary for training and testing purposes.When the method has been thoroughly trained with the data collected,it is used for additional cells cycle tests to predict their SoC.The simulation has been conducted for two different Li-ion battery datasets.According to the experimental data,the suggested DNN-based SoC estimate approach produces a low mean absolute error and root-mean-square-error values,say less than 5%errors.

Effect of Oxidation-Induced Material Parameter Variation on the High Temperature Oxidation Behavior of Nickel

In high temperature oxidation environment, the oxidation reaction will induce variations in material parameters, such as Young's modulus, thermal expansion coefficient (CTE), coefficient of oxygen diffusion (COD), etc. The oxidation -induced material parameter variations should be considered in high temperature mechanical analysis. In this paper, high temperature oxidation behavior of an oxide film/metal substrate system was investigated through a modified phase field approach. The oxidative stress and oxidation weight gain induced by high temperature oxidation were studied. Effects of Young's modulus, COD and CTE on oxidative stress in the oxide film were studied particularly. The simulation results showed that a better agreement with the experimental results could be obtained when considering the oxidation -induced material parameter variations in the high temperature mechanical analysis of oxide film/metal substrate system. The simulation results demonstrated that oxidative stress and oxidation weight gain were more sensitive to the variation of Young's modulus than to the variations of COD and CTE.

Variation of Parameters Formula and Gronwall Inequality for Differential Equations with a General Piecewise Constant Argument

A variation of parameters formula and Gronwall type integral inequality are proved for a differential equation involving general piecewise alternately advanced and retarded argument.

Variation of Parameters Method for Solving System of NonlinearVolterra Integro-Differential Equations

It is well known that nonlinear integro-differential equations play vital role in modeling of many physical processes,such as nano-hydrodynamics,drop wise condensation,oceanography,earthquake and wind ripple in desert.Inspired and motivated by these facts,we use the variation of parameters method for solving system of nonlinear Volterra integro-differential equations.The proposed technique is applied without any discretization,perturbation,transformation,restrictive assumptions and is free from Adomian’s polynomials.Several examples are given to verify the reliability and efficiency of the proposed technique.

Ma’s Variation of Parameters Method for Fisher’s Equations

In this paper,we apply Ma’s variation of parameters method(VPM)for solving Fisher’s equations.The suggested algorithm proved to be very efficient and finds the solution without any discretization,linearization,perturbation or restrictive assumptions.Numerical results reveal the complete reliability of the proposed VPM.

Study on Variation of Parameters Formula and Stability for Impulsive Time－Delay Nonlinear Large Scale Systems

This work concerns the representation and stability properties of impulsive solutions for a class of time-delay and measure nonlinear large scale systems. On the basis of fundamental solution of the correspollding ordinary time-delay nonlinear large scale systems is established.By lumped Picard and Gauss-Seidel iteration methods which avoided the difficulties of constructing lyapunov functin, the explicit algebraic criteria of exponential stability for the impulsive and time-delay system are obtained.

Artificial frozen orbit control scheme based on J_2 perturbation

Since the inclination of frozen orbit with non-rotation of the perigee that occurs due to J2 perturbation must be equal to the critical inclination, this regulation has restricted the application of frozen orbit a lot. In this paper, we propose two control strategies to eliminate the secular growth of the argument of the perigee for orbits that are not at the critical inclination. One control strategy is using transverse continuous low-thrust, and the other is using both the transverse and the radial continuous low-thrusts. Fuel optimization in the second control strategy is addressed to make sure that the fuel consumption is the minimum. Both strategies have no effect on other orbital parameters’ secular motion. It is proved that the strategy with transverse control could save more energy than the one with radial control. Simulations show that the second control strategy could save 54.6% and 86% of energy, respectively, compared with the two methods presented in the references.

Particle flters for probability hypothesis density flter with the presence of unknown measurement noise covariance

In Bayesian multi-target fltering,knowledge of measurement noise variance is very important.Signifcant mismatches in noise parameters will result in biased estimates.In this paper,a new particle flter for a probability hypothesis density（PHD）flter handling unknown measurement noise variances is proposed.The approach is based on marginalizing the unknown parameters out of the posterior distribution by using variational Bayesian（VB）methods.Moreover,the sequential Monte Carlo method is used to approximate the posterior intensity considering non-linear and non-Gaussian conditions.Unlike other particle flters for this challenging class of PHD flters,the proposed method can adaptively learn the unknown and time-varying noise variances while fltering.Simulation results show that the proposed method improves estimation accuracy in terms of both the number of targets and their states.

Robustness aware high performance high fan-in domino OR logic design

A novel technique using a keeper with a simultaneous low supply voltage and low body voltage is proposed to improve the overall performance of high fan-in OR gates without modifying the physical dimensions of the keeper.Simulation results of a 16-input domino OR gate using 45 nm CMOS technology show that the proposed technique could trade off between a high power/speed efficient operation and the robustness to noise effectively.Also,a Monte Carlo analysis indicates that the proposed domino OR gate is more robust to parameter variation compared to a conventional domino OR gate.

On analytical solution of system of nonlinear fractional boundary value problems associated with obstacle

In this paper,we use the modified variation of parameters method(MVPM),an elegant coupling of variation of parameters method(VPM)and Adomian’s decomposition method(ADM),for finding the analytical solution of system of nonlinear fractional boundary value problems associated with obstacle.Caputo sense of fractional derivative is used to coup up with fractional term.The results are calculated in terms of series with easily computable components.The used technique is quite easy and convenient for such type problems because it has been previously applied over several nonlinear obstacle systems.