Search

Starting from Lorenz System, a simpler system using signum function was obtained, which shows chaotic behavior. The conditions for stability were explained. Lyapunov and bifurcation analyses were carried out to exhibit the chaotic behavior. The system's suitability for circuit realization was shown with an electronic circuit implementation which is based mainly on opamps, whose simulation results were in harmony with Matlab results. Finally, as an application, a random number generator (RNG) scheme was designed, in which binary data were obtained from x , y , z variables. In order to reveal that the RNG scheme is functional, NIST-Test was applied to the obtained binary data. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to optimize electrical systems represented by ordinary differential equations and events, using their frequency spectrum is an important purpose for designers, especially to calculate harmonics. Design/methodology/approach: This paper presents a methodology to achieve this, by using a gradient-based optimization algorithm. The paper proposes to use a time simulation of the electrical system, and then to compute its frequency spectrum in the optimization loop. Findings: The paper shows how to proceed efficiently to compute the frequency spectrum of an electrical system to include it in an optimization loop. Derivatives of the frequency spectrum such as the optimization inputs can also be calculated. This is possible even if the sized system behavior cannot be defined a priori, e.g. when there are static converters or electrical devices with natural switching. Originality/value: Using an efficient sequential quadratic programming optimizer, automatic differentiation is used to compute the model gradients. Frequency spectrum derivatives with respect to the optimization inputs are calculated by an analytical formula. The methodology uses a "white-box" approach so that automatic differentiation and the differential equations simulator can be used, unlike most state-of-the-art simulators. [ABSTRACT FROM AUTHOR]

The study examines the aspect of the work of T.L. Caro that concerns the dualism between the underlying state of disorder and chaos that presides over "atomic" phenomena and the admitted condition that the world can nevertheless be regulated by "natural laws" such as to ensure the observable replicability and continuity of physical phenomena and natural species. Assumption that evidently seems to coincide with the theory of "order and chaos", and more exactly with that one of the "deterministic chaos"; for example that of the dynamical systems described by the systems of equations of the Lotka-Volterra type or of non-linear equations of the "logistic equation" type. With the associated emerging behaviors. [ABSTRACT FROM AUTHOR]

This paper considers the problem of learning the unknown structure of a network with the underlying topology given by a polyforest (a collection of directed trees with potentially multiple roots). The main result is an algorithm that consistently learns the network structure using only second-order statistics of the data. The methodology is robust with respect to the presence of unmeasured (latent) nodes: the algorithm detects the exact number and location of the latent nodes, when they satisfy specific degree conditions in the actual network graph. It is shown that the same degree conditions are also necessary for a consistent reconstruction. Thus, the proposed reconstruction algorithm achieves the fundamental limitations in learning the structure of a polyforest network of linear dynamic systems in the presence of latent nodes. This paper overcomes the limitations of previous results that only addressed single-rooted trees, tackling the problem in an efficient way since the computational complexity of the derived algorithm is proven to be polynomial in the number of observed nodes. [ABSTRACT FROM AUTHOR]

This work focuses on a new state estimation problem for dynamic systems with future constraints. It is well known that constraints, as a priori , should always be satisfied by states of some dynamic systems, and thus sufficiently fusing the valuable information into filters will produce more accurate estimates. To this end, a particle smoothing framework is proposed by incorporating future constraints, instead of only current constraints. Next, we construct a criterion function by making the center value of dynamic model satisfy constraints to improve dynamic modeling accuracy, and investigate a cost function to compensate for the impact of the modified dynamic model on the original predicted distribution. Based on this, we present a new particle filter that future constraints are applied in importance sampling and updating particle weights. Especially, the modified dynamic model is chosen as the importance density function so that the sampled particles satisfy constraints at consecutive times as much as possible. Finally, two simulations verify the superiority of the proposed filter. [ABSTRACT FROM AUTHOR]

A non-linear analytical method is presented for global placement of logic cells in an IC, based on algorithms inspired in Dynamic Systems Theory, also known as Chaotic Systems. The related developed tool is called Chaotic Place. The two-dimensional structure of the cells of a circuit was obtained by the reconstruction of a Strange Attractor (Takens’ Theorem). The experiment was tested in the field programmable gate arrays (FPGAs) using the “FPGA Place-and-Route Challenge” benchmarks. For comparison of results, the Half-Perimeter-Wire-Length (HPWL) was used as the main metric. The experiment results show a 6% reduction in wirelength, on average, when compared to the state-of-the-art placement tools for homogeneous FPGAs. [ABSTRACT FROM AUTHOR]

The objective of this paper is to propose a method for evaluating fault identifiability in linear discrete time-varying systems. The basic idea of this method is to quantify the difficulty in estimating an unknown value from an observation for the constructed moving window time-varying model. The analysis of the connection among fault detectability, fault isolability, and fault identifiability is presented in terms of the corresponding measures, distinguishability, and estimability, respectively. Furthermore, factors that influence the performances are analyzed, and an approach for selecting a better system configuration is proposed based on the Fisher information matrix. Finally, the effectiveness of the proposed method in terms of qualitative and quantitative analyses is illustrated through two examples. [ABSTRACT FROM AUTHOR]

Fractional calculus is at this stage an arena where many models are still to be introduced, discussed and applied to real world applications in many branches of science and engineering where nonlocality plays a crucial role. Although researchers have already reported many excellent results in several seminal monographs and review articles, there are still a large number of non-local phenomena unexplored and waiting to be discovered. Therefore, year by year, we can discover new aspects of the fractional modeling and applications. This review article aims to present some short summaries written by distinguished researchers in the field of fractional calculus. We believe this incomplete, but important, information will guide young researchers and help newcomers to see some of the main real-world applications and gain an understanding of this powerful mathematical tool. We expect this collection will also benefit our community. [ABSTRACT FROM AUTHOR]

Mineral extraction activities and the commercialisation of mineral-based products in later stages are fundamental for economic, technological and social development, so understanding their long-term market behaviour in order to forecast prices is crucial for governments, companies and society. Mineral commodity markets are multidimensional as they are driven by the dynamic evolution of financial, technological, psychological and geopolitical factors. Thus, identifying the key features governing mineral commodity prices and modelling their long-term behaviour is an intricate problem that becomes even more complex when the relationship with time is also considered. Although several techniques are available to represent the behaviour and reduce the dimensionality of data sets, these techniques often neglect the temporal relationship and evolution of variables. In many cases, the selection of key variables is solely based on the correlation with each other, relevance and degree of variance, and the cause and effect behaviour of the time-relation of variables, is neglected. This is a critical issue in assessing dynamic systems, especially those involving human behaviour such as social sciences and biology where learning and cognition capacities evolve through time. In this sense, before any attempt to forecast mineral commodity prices, a proper understanding of the embedding dimension and time delay of the variables governing the system is fundamental to determining the number of key features driving the system and the extension of the delayed effects of changes in the initial conditions, respectively. Determining these parameters may become even more complicated because of data scarcity, since the high cost, technical or temporal limitations often hamper obtaining large data sets related to complex dynamic systems that occur in nature and the social sciences. Daily and monthly quotations have been commonly used to represent the dynamics of mineral commodity markets and predict prices, yet they are not sufficient to capture and understand the dynamic evolution of prices in the long-term. These quotations are too short as the delayed effects that reflect on the entire economy and arises from changes in macroeconomic variables can normally be perceived about a year ahead, and may last for up to six years. However, chaos theory has provided valuable tools to assess the dynamics of complex systems allowing the proper determination of the embedding parameters (dimension and time delay), even when using small data sets. This paper examines the long-term dynamics of mineral commodity prices via chaos theory based on a short data set of annual copper prices observed between 1900 and 2015. Copper was used as a study case because it is one of the most competitive markets and representative of mineral commodities traded worldwide. It was found that the dynamic-deterministic behaviour of annual copper prices is embedded in a high-dimensional space that fluctuates between five and seven, and a relatively short time delay between two and three periods. Our finding argues for the use of chaos theory as an important technique to assess the long-term behaviour of mineral commodity prices using short data sets because it improves the understanding of those complex dynamic systems and provides important guidelines that remarkably simplifies the forecasting task. [ABSTRACT FROM AUTHOR]

The lack of particle diversity is a vital problem in particle filtering for nonlinear dynamic systems with unknown noise statistics. In this paper, cost reference particle filter with multi-probability distribution (CRPF_MPD) is introduced to minimize the effects of the lack of particle diversity and to obtain more realistic state estimations. The core of multi-probability distribution is that two subsets are parallelly initialized and resampled by the processes of cost reference particle filter (CRPF) and are respectively updated with different distributions. Information interaction and particle selection form a set of particles with multi-probability distribution to estimate the more realistic states of systems. CRPF_MPD relies on multi-probability distribution, information interaction and particle selection to have excellent performance. As can be seen from the results of simulations, CRPF_MPDs can enhance the accuracy of state estimation and are more robust to different systems. Thus, CRPF_MPDs are available for dynamic systems with unknown noise statistics. • An estimation framework with multi-probability distribution based on the CRPF algorithm is proposed. • A resampling mechanism based on information interaction and particle selection is introduced. • The states of a 1D model and a 2D positioning model are estimated by the proposed method under complex conditions. • The proposed method has excellent accuracy and robustness for non-linear dynamic systems with unknown noise. [ABSTRACT FROM AUTHOR]

Capturing heterogeneous dynamic systems in a probabilistic model is a challenging problem. A single time granularity, such as employed by dynamic Bayesian networks, provides insufficient flexibility to capture the dynamics of many real-world processes. The alternative is to assume that time is continuous, giving rise to continuous time Bayesian networks. Here the problem is that the level of temporal detail is too precise to match available probabilistic knowledge. In this paper, we present a novel class of models, called hybrid time Bayesian networks, which combine discrete-time and continuous-time Bayesian networks. The new formalism allows us to more naturally model dynamic systems with regular and irregularly changing variables. We also present a mechanism to construct discrete-time versions of hybrid models and an EM-based algorithm to learn the parameters of the resulting BNs. Its usefulness is illustrated by means of a real-world medical problem. [ABSTRACT FROM AUTHOR]

Variability is a term that is gaining traction in the tennis coaching world; traditional approaches which emphasise either a oneapproach- fits-all 'text'-book' model of instruction are being abandoned as a result of the acknowledgement that people have differences and the acknowledgement that even the top players show variability. This article summarises some of the different types of variability that might occur in tennis practice, and gives recommendations for coaches. [ABSTRACT FROM AUTHOR]

Abstract: We investigate probability distributions in dynamic multi-mode electromagnetic cavities, commonly referred to as mode-stirred reverberation chambers. We show that Bessel and Bessel distributions play a prominent role when a large but finite number of excited modes, loss of energy (through aperture leakage or dissipation), or nonstationary transient fields are involved. With the aim at reducing the number of simultaneously excited cavity modes as much as possible while maintaining a well-characterizable quasi-random field, measurement results indicate that single-mode stirring is feasible at certain frequencies well below the usual ‘lowest usable frequency’ of the cavity. Distributions for nonstationary fields are shown to allow for improved estimation of the maximum-to-mean ratio of the received power during stepwise rotation of the mode stirrer. [Copyright &y& Elsevier]

Abstract: The parameter identifiability problem for dynamic system ODE models has been extensively studied. Nevertheless, except for linear ODE models, the question of establishing identifiable combinations of parameters when the model is unidentifiable has not received as much attention and the problem is not fully resolved for nonlinear ODEs. Identifiable combinations are useful, for example, for the reparameterization of an unidentifiable ODE model into an identifiable one. We extend an existing algorithm for finding globally identifiable parameters of nonlinear ODE models to generate the ‘simplest’ globally identifiable parameter combinations using Gröbner Bases. We also provide sufficient conditions for the method to work, demonstrate our algorithm and find associated identifiable reparameterizations for several linear and nonlinear unidentifiable biomodels. [Copyright &y& Elsevier]

Abstract: The present work proposes a complementary pair of orthogonal triangular function (TF) sets derived from the well-known block pulse function (BPF) set. The operational matrices for integration in TF domain have been computed and their relation with the BPF domain integral operational matrix is shown. It has been established with illustration that the TF domain technique is more accurate than the BPF domain technique as far as integration is concerned, and it provides with a piecewise linear solution. As a further study, the newly proposed sets have been applied to the analysis of dynamic systems to prove the fact that it introduces less mean integral squared error (MISE) than the staircase solution obtained from BPF domain analysis, without any extra computational burden. Finally, a detailed study of the representational error has been made to estimate the upper bound of the MISE for the TF approximation of a function of Lebesgue measure. [Copyright &y& Elsevier]

Fuzzy logic adds a dynamic element to virtual reality. The world of sharks and dolphins illustrate a model of a fuzzy virtual world Most virtual reality (VR) systems are static. […]

In the conclusion to our discussion of dynamic SQL, we see how ANSI's SQL-92 extends traditional approaches, building a foundation for open, standard portability ALL SQL IMPLEMENtations have offered a […]

As more money managers become disillusioned with modern portfolio theory, some are turning to ideas like chaos and dynamical systems to guide their investment strategies. It is a tantalizing term: […]

• In this study we model a complex fluid dynamics behaviour using the low-ordered simplified nonlinear discrete model. • The current complex phenomena of the coupling iteration between fluid and solid mechanics has the high-order-terms or huge calculations, for example CFD. • We examine changes the theoretical model and different equation from the discrete mechanics with bifurcation based on chaos theory and post-buckling theory. • We obtain approximate results from both experimental data and present method in global view. • We forecast this complex phenomena using global bifurcation diagram based on non-equilibrium discrete mechanics by this present model. The dynamic bifurcation analysis of the nonlinear oscillation of a simple fluidelastic structure is presented. This structure is a cantilever beam in a flow, and it behaves as a nonlinear system without potential energy. The structure demonstrates complex flutter behaviour that varies with the controlled flow velocity. We observe the flutter behaviour in a flow experiment, and the motion is characterised with this present model based on chaos theory of discrete dynamics. We can readily find the solution of the simple system, with which it is possible to create a map of the complex flutter behaviour. [ABSTRACT FROM AUTHOR]

• A predictive COVID-19 model is considered. • The second wave of COVID-19 in Iran is studied. • Some predictive results of the peak epidemic outbreak are given. • Estimated times of the end of the epidemic in Iran in several scenarios are approximated in the plots. • The second wave of COVID-19 is predicated to happen between August and December 2020. One of the common misconceptions about COVID-19 disease is to assume that we will not see a recurrence after the first wave of the disease has subsided. This completely wrong perception causes people to disregard the necessary protocols and engage in some misbehavior, such as routine socializing or holiday travel. These conditions will put double pressure on the medical staff and endanger the lives of many people around the world. In this research, we are interested in analyzing the existing data to predict the number of infected people in the second wave of out-breaking COVID-19 in Iran. For this purpose, a model is proposed. The mathematical analysis corresponded to the model is also included in this paper. Based on proposed numerical simulations, several scenarios of progress of COVID-19 corresponding to the second wave of the disease in the coming months, will be discussed. We predict that the second wave of will be most severe than the first one. From the results, improving the recovery rate of people with weak immune systems via appropriate medical incentives is resulted as one of the most effective prescriptions to prevent the widespread unbridled outbreak of the second wave of COVID-19. [ABSTRACT FROM AUTHOR]

Many Windows programmers consider DLLs difficult to understand or write and so avoid creating them. Actually, DLLs differ from Windows applications mainly in two respects: a different compilation option is […]