Including Time Delay Research Articles

A dynamic network model of temporal receptive fields in primary auditory cortex.

Auditory neurons encode stimulus history, which is often modelled using a span of time-delays in a spectro-temporal receptive field (STRF). We propose an alternative model for the encoding of stimulus history, which we apply to extracellular recordings of neurons in the primary auditory cortex of anaesthetized ferrets. For a linear-non-linear STRF model (LN model) to achieve a high level of performance in predicting single unit neural responses to natural sounds in the primary auditory cortex, we found that it is necessary to include time delays going back at least 200 ms in the past. This is an unrealistic time span for biological delay lines. We therefore asked how much of this dependence on stimulus history can instead be explained by dynamical aspects of neurons. We constructed a neural-network model whose output is the weighted sum of units whose responses are determined by a dynamic firing-rate equation. The dynamic aspect performs low-pass filtering on each unit’s response, providing an exponentially decaying memory whose time constant is individual to each unit. We find that this dynamic network (DNet) model, when fitted to the neural data using STRFs of only 25 ms duration, can achieve prediction performance on a held-out dataset comparable to the best performing LN model with STRFs of 200 ms duration. These findings suggest that integration due to the membrane time constants or other exponentially-decaying memory processes may underlie linear temporal receptive fields of neurons beyond 25 ms.

Complementary constraints on dark energy equation of state from strongly lensed gravitational wave

It has been shown that time delay of strong gravitational lensing is not only an effective cosmological probe to constrain the Hubble constant, the matter density and the curvature of the universe but also useful for breaking the degeneracy of the dark energy equation of state and thus provide complementarity with other popular probes, such as type Ia supernovae, baryon acoustic oscillations, and cosmic microwave background radiation. Interestingly, compared to traditional strong lensing systems where quasars act as sources, strongly lensed gravitational waves (GWs) from compact binary coalescence and their electromagnetic (EM) counterparts systems have been recently proposed to be more powerful for studying cosmology since GWs and their EM counterparts are transients. Short durations of GWs and their EM counterparts are very advantageous to time delay measurement and lens profile modeling. Here, in the framework of Chevalier-Polarski-Linder (CPL) parametrization, we investigate improvement of constraining power on dark energy equation of state due to including time delay measurements of strong lensed GW systems. It is suggested that, on the basis of the third generation ground-based detector, e.g. Einstein Telescope, adding time delay of only 30 strong lensed GW systems to type Ia supernovae and cosmic microwave background radiation can improve the dark energy figure of merit by a factor 2. For the traditional standard siren method where the uncertainties of luminosity distances of GWs are $\sim10\%$, a few $\times~10^4$ events are expected to present similar constraints. In the precision cosmology era, this progress is of great significance for studying the nature of dark energy.

Modeling multi-group dynamics of related viral videos with delay differential equations

Epidemic models have previously been employed to better understand the spread of internet content, such as individual viral videos. Motivated by geographical differences between viewing populations, as well as by multiple viral videos which are linked or related in some way, we propose a multi-group susceptible–exposed–infected–recovered–susceptible (SEIRS) delay differential equation epidemic model for the popularity evolution of viral videos. The model accounts for the multi-group environment via (in general, heterogeneous) networks of single-group SEIRS equations. Existence and stability conditions for disease-free and endemic equilibrium states are obtained, while numerical simulations demonstrate the emergence of non-symmetric endemic equilibrium states across the network — in the case of heterogeneous parameters. In order to demonstrate the effectiveness of our modeling approach, we compare solutions to our model with data obtained from coupled YouTube videos. Our results demonstrate that the inclusion of coupling between such videos allows for better agreement with data than considering each video in isolation. Such results suggest that the multi-group epidemic modeling approach including time delays and coupling between videos is a useful tool for understanding the dynamics of viral videos which are connected in some manner. While the proposed network SEIRS differential delay equation epidemic model was applied to viral video data, it may be applicable to a wide variety of internet content and, more generally, may be used to model information propagation within and between communities under the assumption of time delays in information propagation.

To study the incidence and preintervention factors associated with acute kidney injury in patients diagnosed with ureteric calculi.

Aims and Objectives:The study aims to evaluate the incidence and factors associated with acute kidney injury (AKI) among patients presenting with ureteric calculi. We also intend to study the impact of time delay since first symptom to presentation to our hospital among patients with ureteric calculi and its influence on AKI.Material and Method:The study is a prospective observational study and included all symptomatic ureteric calculi patients. AKI was defined as per the KDIGO guidelines. All the patients diagnosed with ureteric calculi were grouped into those having an episode of AKI and those without an episode on AKI.Results:The incidence of AKI in our study was 14.63% (18 patients) among 123 patients of ureteric calculi. Average time delay from time of diagnosis to presentation among patients with AKI was 31.7±6.2 days (mean ± S.D) as compared to 19.5±5.7 (mean ± S.D) days among all cases. Factors which were significantly associated with AKI in patients with ureteric calculi include time delay, diabetes mellitus, bilateral ureteric calculi, stone size greater than 10 mm, solitary functioning kidney and urine culture showing gram negative growth. Fifty percent of the AKI group eventual required nephrectomy of one renal unit.Conclusion:This study will help us streamline our resources predominantly towards those patients who present with factors associated with increased risk of AKI. As the time delay to presentation in patients with AKI with ureteric calculi is significantly higher, it is imperative to counsel patients with stone disease.

On the stability of two neuron populations interacting with each other

In this study, we deal with stability for the linearized neural field model for two neuron populations. We determine the asymptotic stability region by using the D-subdivision method for different delay terms including time delays. Also, we find the number of unstable characteristic exponents for the unstable regions. We observe that the stability region for the model becomes smaller as the delay term $\tau $ increases.

Global analysis and numerical simulations of a novel stochastic eco-epidemiological model with time delay

In this paper, a new stochastic eco-epidemiological model is proposed and investigated, and the high dimensional model includes time delay and a general incidence rate which make the study more complex. First, the existence and uniqueness of the global positive solution with any positive initial value are verified. Second, using stochastic analysis methods and some differential inequality techniques, we explore the long-time asymptotic properties of the stochastic delayed system. Furthermore, we prove that the solution of the stochastic delayed system has a unique stationary distribution and it has ergodic property. Third, the sufficient conditions of permanence in mean or extinction for the ecological populations are obtained. Finally, we introduce a series of computer simulations to show the performance of the theoretical results.

Useful redundancy in parameter and time delay estimation for continuous-time models

This paper proposes an algorithm to estimate the parameters, including time delay, of continuous time systems based on instrumental variable identification methods. To overcome the multiple local minima of the cost function associated with the estimation of a time delay system, we utilise the useful redundancy technique. Specifically, the cost function is filtered through a set of low-pass filters to improve convexity with the useful redundancy technique exploited to achieve convergence to the global minimum of the optimization problem. Numerical examples are presented to demonstrate the effectiveness of the proposed algorithm.

A comprehensive survey on the reliability of mobile wireless sensor networks: Taxonomy, challenges, and future directions

With the development and popularization of mobile terminal technology, mobile wireless sensor networks (MWSNs) have become a new evolution trend in wireless sensor networks (WSNs) technology. The mobility of nodes introduced by MWSNs greatly expands the application range of WSNs. However, the mobility of the sink node also induces changes of the network topology, time delays, and packet loss rates, which can greatly affect the routing performance of the networks. In addition, the reliability and robustness of the networks are also greatly affected and challenged. The theories and methods applied to WSNs previously, such as data collection, reliable data transmission, network reliability, network topologies, and routing protocols are not currently available for MWSNs. The introduction of mobility features into traditional static WSNs brings new challenges for the stability, security, and reliability of WSNs. Reliability is an important index for evaluating the performance of MWSNs. Moreover, the reliability of the data transmission determines the practical value of MWSNs. The stable and reliable operation of MWSNs requires ongoing and important work. Therefore, in this article, we present a comprehensive and meticulous investigation of the reliability theory of MWSNs which was developed in recent years. This article outlines the classification and features of MWSNs. Specifically, we systematically analyze the research direction and recent progress made in the field of MWSNs. The existing methods are systematically compared and the advantages and disadvantages of the methods are presented. The main parameters of comparison include time delays, network size, energy efficiency, scalability, and reliability. Finally, some open questions and future research directions are presented at the end of this article.

Control design for a switched system including time delay depending on input polarity and its application to a pneumatic isolation table

Control design for a switched system including time delay depending on input polarity and its application to a pneumatic isolation table

Extension of an Anti-windup Scheme for Systems with Time Delay and Integral Action

This study extends a recent anti-windup scheme by using Smith predictor based controller approach and by redesigning the transfer functions within the anti-windup structure. We present simulation studies for a system including time delay and integrator to illustrate that our extended structure successfully accomplish accurate tracking under the saturation nonlinearity.

Investigation of Copper–Carbon Nanotube Composites as Global VLSI Interconnects

Applicability of copper–carbon nanotube (Cu-CNT) composites as on-chip global VLSI interconnects is investigated comprehensively. Electrical modeling of Cu-CNT composite interconnects is carried out by virtue of effective complex conductivity. The performances, including time delay and step response, are characterized based on the equivalent circuit model. Finally, the crosstalk effect between coupled Cu-CNT composite interconnects is analyzed.

Optimal Control of a One-Area LFC System Including Time Delay Using Shuffled Frog Leaping Algorithm

This paper proposes the shuffled frog leaping algorithm (SFLA) to fine tune a proportional-integral (PI) controller in a load frequency control (LFC) system with time delay. The SFLA code is built using MATLAB environment. The effectiveness of the SFLA-PI controller is compared with that obtained using a genetic algorithm-based PI controller. The validity of the proposed controller is extensively validated by the simulation results that are carried out using PSCAD/EMTDC program.

Estimating the parameters of neural mass models including time delay and nonlinearity using a particle filter: a preliminary study toward model‐based EEG analysis

Electroencephalogram (EEG) and local field potential (LFP) signals are measured for both experimental and clinical purposes which include sleep stage analyses, brain–computer interfaces, and disease diagnosis. EEG and LFP data analyses are typically based on models assuming that the measured data is generated from a biological system and estimate the model parameter values that most accurately reproduce the measured data. Thus, use of a biologically plausible model is important for a model‐based analysis. However, analyses using models that include time delay and nonlinearity have not been reported, even though they are biologically important for EEG generation mechanisms. In this study, we developed a parameter estimation method that uses a particle filter for models with time delay and nonlinearity, which was evaluated with simulations. Simulated EEG data were generated from neural mass models (NMMs). The NMM parameters were estimated from the generated data. Furthermore, parameters for modeling EEG features of patients with Alzheimer's disease were included in the NMM; the disease parameters were estimated from the simulated EEG data. We observed that NMM parameters, as well as the disease parameters, were accurately estimated from the simulated data. We conclude that the validity of our method for estimating parameters of NMMs including time delay and nonlinearity is confirmed for simulated EEG data, and these results show the possibility of using our method for model‐based analysis with real EEG data. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Policy Development for the Energy Mix in Indonesia Using System Dynamics

Objective - This paper discusses a literature review regarding finding system dynamics modeling as the preferred approach to building the national energy system model in Indonesia and introduces the uniqueness of the initial system dynamics model of the Indonesia energy mix today. Methodology/Technique - A literature review about system modeling of energy portfolio management worldwide to find the research gaps and to screen for the preferred modeling approach for the country. Along with past statistics in the background, a combination of system dynamics modeling and focus group discussion is subsequently expected to answer the research questions, bridge the research gaps, and contribute a new invention to management science. Findings - The theoretical testing reveals that system dynamics modeling is suitable to simplify and simulate very large, complex dynamic systems of energy supply that get feedback from many subsystems in non-linear fashions and is a good methodology for holistic approaches to understand underlying behavior over time, taking into account all sorts of feedback, including time delays and feedback loops, and those cannot be easily represented by conventional models, vastly applied in a study of sustainable development. Novelty - The uniqueness of the proposed system dynamics approach lies in the inclusion of a series of new variables developed from common characteristic impediments in public policy development using a traditional non-simulation approach, besides its focus on the unprecedented energy supply quality side of the archipelagic country with its unique parameters being highlighted. Type of Paper: Review Keywords: Portfolio Management; Past Performance; System Dynamic Modelling; Initial Model of Energy Close Loop Diagram of Indonesia Today. JEL Classification: Q40, Q48.

Global synchronization in finite time for fractional-order neural networks with discontinuous activations and time delays

This paper is concerned with the global Mittag-Leffler synchronization and the synchronization in finite time for fractional-order neural networks (FNNs) with discontinuous activations and time delays. Firstly, the properties with respect to Mittag-Leffler convergence and convergence in finite time, which play a critical role in the investigation of the global synchronization of FNNs, are developed, respectively. Secondly, the novel state-feedback controller, which includes time delays and discontinuous factors, is designed to realize the synchronization goal. By applying the fractional differential inclusion theory, inequality analysis technique and the proposed convergence properties, the sufficient conditions to achieve the global Mittag-Leffler synchronization and the synchronization in finite time are addressed in terms of linear matrix inequalities (LMIs). In addition, the upper bound of the setting time of the global synchronization in finite time is explicitly evaluated. Finally, two examples are given to demonstrate the validity of the proposed design method and theoretical results.

Rapid satellite capture by a space robot based on delay compensation

PurposeRapid satellite capture by a free-floating space robot is a challenge problem because of no-fixed base and time-delay issues. This paper aims to present a modified target capturing control scheme for improving the control performance.Design/methodology/approachFor handling such control problem including time delay, the modified scheme is achieved by adding a delay calibration algorithm into the visual servoing loop. To identify end-effector motions in real time, a motion predictor is developed by partly linearizing the space robot kinematics equation. By this approach, only ground-fixed robot kinematics are involved in the predicting computation excluding the complex space robot kinematics calculations. With the newly developed predictor, a delay compensator is designed to take error control into account. For determining the compensation parameters, the asymptotic stability condition of the proposed compensation algorithm is also presented.FindingsThe proposed method is conducted by a credible three-dimensional ground experimental system, and the experimental results illustrate the effectiveness of the proposed method.Practical implicationsBecause the delayed camera signals are compensated with only ground-fixed robot kinematics, this proposed satellite capturing scheme is particularly suitable for commercial on-orbit services with cheaper on-board computers.Originality/valueThis paper is original as an attempt trying to compensate the time delay by taking both space robot motion predictions and compensation error control into consideration and is valuable for rapid and accurate satellite capture tasks.

Strong gravitational lensing for the photons coupled to a Weyl tensor in a Kerr black hole spacetime

We present firstly equation of motion for the photon coupled to Weyl tensor in a Kerr black hole spacetime and then study further the corresponding strong gravitational lensing. We find that black hole rotation makes propagation of the coupled photons more complicated, which brings some new features for physical quantities including the marginally circular photon orbit, the deflection angle, the observational gravitational lensing variables and the time delay between two relativistic images. There is a critical value of the coupling parameter for existence of the marginally circular photon orbit outside the event horizon, which depends on the rotation parameter of black hole and the polarization direction of photons. As the value of coupling parameter is near the critical value, we find that the marginally circular photon orbit for the retrograde photon increases with the rotation parameter, which modifies a common feature of the marginally circular photon orbit in a rotating black hole spacetime since it always decreases monotonously with the rotation parameter in the case without Weyl coupling. Combining with the supermassive central object in our Galaxy, we estimated the observables including time delays between the relativistic images in the strong gravitational lensing as the photons couple to Weyl tensor.

Extended dissipativity of generalised neural networks including time delays

ABSTRACTThis article explores the extended dissipativity conditions for generalised neural networks (GNNs) including interval time-varying delays. Extended dissipativity criterions are proposed by making proper Lyapunov–Krasovskii functional. The improved reciprocally convex combination and weighted integral inequality techniques are together applied in main results to establish the new extended dissipativity conditions of delayed GNNs. Finally, the feasibility and superiority of the proposed novel approach is clearly shown by numerical examples.

ネットワークベース系におけるパケットロスと変動時間遅れを考慮した制御系の設計

In this paper, a control system design that considers packet losses and time delay in a network-based control system is proposed. A conventional communication observer is exploited to compensate for time delay; however, it does not consider packet losses. Furthermore, when a modeling error exists, steady-state errors occur. Therefore, in order to compensate for the packet loss and the modeling error, a model error feedback system that does not include time delay is proposed. The proposed system was evaluated by numerical simulations with model error and packet loss.

Bifurcation Analysis of a Modified Tumor-immune System Interaction Model Involving Time Delay

We study stability and Hopf bifurcation analysis of a model that refers to the competition between the immune system and an aggressive host such as a tumor. The model which describes this competition is governed by a reaction-diffusion system including time delay under the Neumann boundary conditions, and is based on Kuznetsov-Taylor's model. Choosing the delay parameter as a bifurcation parameter, we first show that Hopf bifurcation occurs. Second, we determine two properties of the periodic solution, namely its direction and stability, by applying the normal form theory and the center manifold reduction for partial functional differential equations. Furthermore, we discuss the effects of diffusion on the dynamics by analyzing a model with constant coefficients and perform some numerical simulations to support the analytical results. The results show that diffusion has an important effects on the dynamics of a mathematical model.