A Novel Statistical Delay Model Based on the Birnbaum-Saunders Distribution for RLC Interconnects in 90nm Technologies

For performance optimization such as placement,interconnect synthesis,and routing, an efficient and accurate interconnect delay metric is critical,even in design tools development like design for yield （DFY） and design for manufacture （DFM）. In the nanometer regime, the recently proposed delay models for RLC interconnects based on statistical probability density function （PDF）interpretation such as PRIMO,H-gamma,WED and RLD bridge the gap between accuracy and efficiency. However, these models always require table look-up when operating. In this paper, a novel delay model based on the Birnbaum-Saunders distribution （BSD） is presented. BSD can accomplish interconnect delay estimation fast and accurately without table look-up operations. Furthermore, it only needs the first two moments to match. Experimental results in 90nm technology show that BSD is robust, easy to implement,efficient,and accurate.

Effects of delayed repair of peripheral nerve injury on the spatial distribution of motor endplates in target muscle

Motor endplates(MEPs) are important sites of information exchange between motor neurons and skeletal muscle, and are distributed in an organized pattern of lamellae in the muscle. Delayed repair of peripheral nerve injury typically results in unsatisfactory functional recovery because of MEP degeneration. In this study, the mouse tibial nerve was transected and repaired with a biodegradable chitin conduit, immediately following or 1 or 3 months after the injury. Fluorescent α-bungarotoxin was injected to label MEPs. Tissue optical clearing combined with light-sheet microscopy revealed that MEPs were distributed in an organized pattern of lamellae in skeletal muscle after delayed repair for 1 and 3 months. However, the total number of MEPs, the number of MEPs per lamellar cluster, and the maturation of single MEPs in gastrocnemius muscle gradually decreased with increasing denervation time. These findings suggest that delayed repair can restore the spatial distribution of MEPs, but it has an adverse effect on the homogeneity of MEPs in the lamellar clusters and the total number of MEPs in the target muscle. The study procedures were approved by the Animal Ethics Committee of the Peking University People's Hospital(approval No. 2019 PHC015) on April 8, 2019.

Grey series time-delay predicting model in state estimation for power distribution networks

A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.

A Note on a One-Parameter Weibull Distributed Deteriorating Item EOQ Inventory Model with Varying Quadratic Demand and Delay in Payments

In this paper, an EOQ inventory model is developed for deteriorating items with variable rates of deterioration and conditions of grace periods when demand is a quadratic function of time. The deterioration rate considered here is a special type of Weibull distribution deterioration rate, i.e., a one-parameter Weibull distribution deterioration rate and it increases with respect to time. The quadratic demand precisely depicts of the demand of seasonal items, fashion apparels, cosmetics, and newly launched essential commodities like android mobiles, laptops, automobiles etc., coming to the market. The model is divided into three policies according to the occurrence of the grace periods. Shortages, backlogging and complete backlogging cases are not allowed to occur in the model. The proposed model is well-explained with the help of a simple solution procedure. The three numerical examples are taken to illustrate the effectiveness of the EOQ inventory model along with sensitivity analysis.

Oscillation of Solutions for a Class of Nonlinear Neutral Partial Differential Equations with Continuous Distribution Delay

In this paper, some sufficient conditions are obtained for the oscillation of solutions for a class of second order nonlinear neutral partial differential equations with continuous distribution delay under Robin and Dirichlet＇s boundary value conditions.

Statistical delay distribution analysis on high-speed railway trains

The focus of this study is to explore the statis-tical distribution models of high-speed railway (HSR) train delays. Based on actual HSR operational data, the delay causes and their classification, delay frequency, number of affected trains, and space–time delay distributions are discussed. Eleven types of delay events are classified, and a detailed analysis of delay distribution for each classifica-tion is presented. Models of delay probability delay prob-ability distribution for each cause are proposed. Different distribution functions, including the lognormal, exponen-tial, gamma, uniform, logistic, and normal distribution, were selected to estimate and model delay patterns. The most appropriate distribution, which can approximate the delay duration corresponding to each cause, is derived. Subsequently, the Kolmogorov–Smirnov (K–S) test was used to test the goodness of fit of different train delay distribution models and the associated parameter values. The test results show that the distribution of the test data is consistent with that of the selected models. The fitting distribution models show the execution effect of the timetable and help in finding out the potential conflicts in real-time train operations.

Exponential stability criteria on neural networks with continuously distributed delays

The exponential stability of a class of neural networks with continuously distributed delays is investigated by employing a novel Lyapunov-Krasovskii functional. Through introducing some free-weighting matrices and the equivalent descriptor form, a delay-dependent stability criterion is established for the addressed systems. The condition is expressed in terms of a linear matrix inequality （LMI）, and it can be checked by resorting to the LMI in the Matlab toolbox. In addition, the proposed stability criteria do not require the monotonicity of the activation functions and the derivative of a time-varying delay being less than 1, which generalize and improve earlier methods. Finally, numerical examples are given to show the effectiveness of the obtained methods.

Neural Dynamics for Distributed Collaborative Control of Manipulators With Time Delays

Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.

GLOBAL STABILITY OF SIRS EPIDEMIC MODELS WITH A CLASS OF NONLINEAR INCIDENCE RATES AND DISTRIBUTED DELAYS

In this article, we establish the global asymptotic stability of a disease-free equilibrium and an endemic equilibrium of an SIRS epidemic model with a class of nonlin- ear incidence rates and distributed delays. By using strict monotonicity of the incidence function and constructing a Lyapunov functional, we obtain sufficient conditions under which the endemic equilibrium is globally asymptotically stable. When the nonlinear inci- dence rate is a saturated incidence rate, our result provides a new global stability condition for a small rate of immunity loss.

A Simple Method for Source Depth Estimation with Multi-path Time Delay in Deep Ocean

A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.

Global stability of Cohen-Grossberg neural networks with time-varying and distributed delays

In this paper, the global asymptotic stability is investigated for a class of Cohen-Grossberg neural networks with time-varying and distributed delays. By using the Lyapunov-Krasovskii functional and equivalent descriptor form of the considered system, several delay-dependent sufficient conditions are obtained to guarantee the asymptotic stability of the addressed systems. These conditions are dependent on both time-varying and distributed delays and presented in terms of LMIs and therefore, the stability criteria of such systems can be checked readily by resorting to the Matlab LMI toolbox. Finally, an example is given to show the effectiveness and less conservatism of the proposed methods.

DYNAMICS OF NEW CLASS OF HOPFIELD NEURAL NETWORKS WITH TIME-VARYING AND DISTRIBUTED DELAYS

In this paper, we investigate the dynamics and the global exponential stability of a new class of Hopfield neural network with time-varying and distributed delays. In fact, the properties of norms and the contraction principle are adjusted to ensure the existence as well as the uniqueness of the pseudo almost periodic solution, which is also its derivative pseudo almost periodic. This results are without resorting to the theory of exponential dichotomy. Furthermore, by employing the suitable Lyapunov function, some delayindependent sufficient conditions are derived for exponential convergence. The main originality lies in the fact that spaces considered in this paper generalize the notion of periodicity and almost periodicity. Lastly, two examples are given to demonstrate the validity of the proposed theoretical results.

ADMM-based Distributed Algorithm for Economic Dispatch in Power Systems With Both Packet Drops and Communication Delays

By virtue of alternating direction method of multipliers(ADMM), Newton-Raphson method, ratio consensus approach and running sum method, two distributed iterative strategies are presented in this paper to address the economic dispatch problem(EDP) in power systems. Different from most of the existing distributed ED approaches which neglect the effects of packet drops or/and time delays, this paper takes into account both packet drops and time delays which frequently occur in communication networks. Moreover, directed and possibly unbalanced graphs are considered in our algorithms, over which many distributed approaches fail to converge. Furthermore, the proposed schemes can address the EDP with local constraints of generators and nonquadratic convex cost functions, not just quadratic ones required in some existing ED approaches. Both theoretical analyses and simulation studies are provided to demonstrate the effectiveness of the proposed schemes.

Delay-dependent stability of linear multistep methods for differential systems with distributed delays

This paper deals with the stability of linear multistep methods for multidimensional differential systems with distributed delays. The delay-dependent stability of linear multistep methods with compound quadrature rules is studied. Several new sufficient criteria of delay-dependent stability are obtained by means of the argument principle. An algorithm is provided to check delay-dependent stability. An example that illustrates the effectiveness of the derived theoretical results is given.

UNIFORM DECAY IN WEAKLY DISSIPATIVE TIMOSHENKO SYSTEM WITH INTERNAL DISTRIBUTED DELAY FEEDBACKS

In this paper we consider one-dimensional Timoshenko system with linear fric- tional damping and a distributed delay acting on the displacement equation. Under suitable assumptions on the weight of the delay and the wave speeds, we establish the well-posedness of the system and show that the dissipation through the frictional damping is strong enough to uniformly stabilize the system even in the presence of delay.

Sliding mode control of uncertain systems with distributed time-delay: parameter-dependent Lyapunov functional approach

The robust stability and robust sliding mode control problems are studied for a class of linear distributed time-delay systems with polytopic-type uncertainties by applying the parameter-dependent Lyapunov functional approach combining with a new method of introducing some relaxation matrices and tuning parameters, which can be chosen properly to lead to a less conservative result. First, a sufficient condition is proposed for robust stability of the autonomic system; next, the sufficient conditions of the robust stabilization controller and the existence condition of sliding mode are developed. The results are given in terms of linear matrix inequalities （LMIs）, which can be solved via efficient interior-point algorithms. A numerical example is presented to illustrate the feasibility and advantages of the proposed design scheme.

A descriptor system approach to robust stabilityof uncertain degenerate systems with discreteand distribute delays

The robust stability of uncertain linear degenerate systems with discrete and distributed delays is studied in this paper. The uncertainties under consideration are norm bounded, and possibly time varying. A novel robust stability criterion of the system is derived by constructing Lyapunov functions. The degenerate systems are transformed to a descriptor system and the stability criteria are formulated in the form of a linear matrix inequality （LMI）. Therefore, it is easy to check the robust stability of the degenerate systems by using this method. Numerical examples are also worked out to illustrate the obtained results.

The Distributed Network Monitoring Model with Bounded Delay Constraints

We address the problem of optimizing a distributed monitoring system and the goal of the optimization is to reduce the cost of deployment of the monitoring infrastructure by identifying a minimum aggregating set subject to delay constraint on the aggregating path. We show that this problem is NP-hard and propose approximation algorithm proving the approximation ratio with lnm+1, where is the number of monitoring nodes. At last we extend our modal with more constraint of bounded delay variation. Key words network - distributed monitoring - delay constraint - NP-hard CLC number TP 393 Foundation item: Supported by the National Natural Science Foundation of China (60373023)Biography: LIU Xiang-hui(1973-), male, Ph. D. candidate, research direction: algorithm complexity analysis, QoS in Internet.

Simulation of a class of delay stochastic system with distributed parameter

Simulation of a class of delay stochastic system with distributed parameter is discussed. Difference schemes for the numerical computation of delay stochastic system are obtained. The precision of the difference scheme and the efficiency of the difference scheme in simulation of delay stochastic system with distributed parameter are analyzed. Examples are given to illustrate the application of the method.

Joint DOA and time delay estimation method for space-time coherent distributed signals based on search

Under dense urban fading environment, performance of joint multi-path parameter estimation method based on traditional point signal model degrades seriously. In this paper, a new space and time signal model based on multipath distribution function is given after new space and time manifold is reconstructed. Then joint spacetime signal subspace is obtained by converting acquired channel from time domain to frequency domain .Then space and time spectrum is formulated by the space sub-matrix and time sub-matrix taken out of joint space-time signal subspace, and parameters are estimated by searching the minimum eigenvalues of the space matrix and the time matrix. Lastly, A space and time parameters matching process is performed by using the orthogonal property between joint noise subspace and the space-time manifold. In contrast with tradition MUSIC, the algorithm we present here only need two 1- dimension searching and was not sensitive to different distribution function.