Sequence Of Impulses Research Articles

Two unequal shots in the same hole: statistical versus deterministic deconvolution

Determination of the source time function and earth impulse response for explosive source seismic reflection data is traditionally performed using predictive deconvolution, which assumes the reflection seismogram is the convolution of a minimum-phase wavelet with a white, random, stationary sequence of impulses. We compare this statistical method with a new deterministic method that uses two unequal shots close together in the same hole and assumes a seismogram is the convolution of a source time function with a Green's function, plus noise. The seismograms from the two shots share essentially the same Green's function to any receiver, because the shots are close together. The Green's function is estimated by deconvolving the two seismograms at a given receiver for the corresponding source time functions, modelled independently; source parameters are obtained by trial-and-error by minimising the difference between the two estimates of the Green's function. We test these competing theories using seismic reflection data acquired with two charges fired separately in the same hole into a receiver spread of 1178 bunched geophone groups at 10 m intervals: a 1 kg charge at 42 m depth and 2 kg at 40 m depth. The criterion for comparison of the theories is the similarity of the recovered impulse responses at any receiver. Each method recovers a wavelet, or source time function, for each shot and two estimates of the impulse response, or Green's function, at each receiver. The Green's functions recovered from the two shots using the deterministic method are almost identical and are measurably more similar than the impulse responses recovered using predictive deconvolution. That is, the deterministic method is better. The resolution of explosive source seismic reflection data can now be significantly improved with the new method and minimal additional field effort of loading one extra charge per shot hole.

Optimization approaches to Wolbachia-based biocontrol

This paper proposes two realistic and biologically viable methods for Wolbachia-based biocontrol of Aedes aegypti mosquitoes, assuming imperfect maternal transmission of the Wolbachia bacterium, incomplete cytoplasmic incompatibility, and direct loss of Wolbachia infection caused by thermal stress. Both methods are based on optimization approaches and allow for the stable persistence of Wolbachia-infected mosquitoes in the wild Ae. aegypti populations in a minimum time and using the smallest quantity of Wolbachia-carrying insects to release. The first method stems from the continuous-time optimal release strategy, which is further transformed into a sequence of suboptimal impulses mimicking instantaneous releases of Wolbachia-carrying insects. The second method constitutes a novel alternative to all existing techniques aimed at the design of release strategies. It is developed using metaheuristics (ϵ-constraint method combined with the genetic algorithm) and directly produces a discrete sequence of decisions, where each element represents the quantity of Wolbachia-carrying mosquitoes to be released instantaneously and only once per a specified time unit. It turns out that a direct discrete-time optimization (second method) renders better quantifiable results compared to transforming a continuous-time optimal release function into a sequence of suboptimal impulses (first method). As an illustration, we provide examples of daily, weekly, and fortnightly release strategies designed by both methods for two Wolbachia strains, wMel and wMelPop.

Input-to-state hybrid impulsive formation stabilization for multi-agent systems with impulse delays

This paper addresses the input-to-state formation stabilization problem of nonlinear multi-agent systems within a hybrid impulsive framework, considering delay-dependent impulses, strong nonlinearity, and deception attack signals. By leveraging Lyapunov functionals, impulsive comparison theory, average impulsive interval methods, and graph theory, we develop novel criteria for possessing locally input-to-state and integral input-to-state formation stabilization across different impulse sequence classes. These criteria are expressed in terms of continuous/impulsive feedback gains, time delay size, nonlinearity strength, uniform upper bound of impulsive interval, and length of average impulsive interval. Notably, the design of control impulses benefit the destabilizing continuous dynamics in the formation stabilization process. To demonstrate the effectiveness and validity of the analytical results, we provide numerical simulation examples involving various types of external attack signals.

Synchronization of Kuramoto-oscillator networks under event-triggered impulsive control with noise perturbation

This paper studies the stochastic average synchronization of Kuramoto-oscillator networks under event-triggered impulsive control (ETIC) strategies, in which the event-triggered mechanism (ETM) determines the impulsive control time sequence. The continuous ETM is designed to avoid the Zeno behavior by continuous measuring, and the periodic ETM is proposed by periodic sampling. Based on the proposed ETIC methods, several sufficient conditions for the stochastic average synchronization of Kuramoto-oscillator networks are established. Unlike time-triggered impulsive control, where the triggered instants are pre-designed, ETIC is activated only upon the occurrence of an event, so synchronization conditions are heavily dependent on the ETM. Furthermore, there is no control input between two successive triggering instants, and the control input is required only at the trigger instants. Finally, numerical simulations are shown to illustrate the effectiveness of the theoretical results. Besides, it is found that the presence of noise may favor the synchronization of Kuramoto-oscillator networks.

Relating state-of-charge to impedance and equivalent circuit parameters in lithium-ion cells: An experimental study

The wide-band impedance of Lithium-ion (Li-ion) batteries has become a focal point for researchers interested in State-of-Charge (SOC) estimation and battery modeling. However, the interplay between SOC, wide-band impedance, and model parameters has not been extensively explored. This paper addresses this gap by investigating how SOC impacts the impedance and Equivalent Circuit Model (ECM) parameters of a Li-ion battery cell through empirical measurements. The study utilizes discharge tests to vary the SOC and employs the Coulomb Counting Method (CCM) to estimate the approximate SOC from the response signals. A novel measurement technique is introduced and applied to determine a cell’s wide-band impedance at different SOC levels. This innovative approach uses a Pseudo-random Impulse Sequence (PRIS) perturbation signal to measure wide-band cell impedance. The collected impedance data is then used to estimate the ECM parameters. Experimental findings reveal an inverse relationship between impedance and SOC. Additionally, the ECM parameters exhibit significant correlation with SOC, particularly in mid- to low-frequency regions. This research highlights that SOC profoundly influences ECM parameters, offering valuable insights into the performance of Li-ion batteries under various conditions.

The Development of Neural Art: An Outline

Abstract Throughout the author’s career, Neural Art, which is based on the functional properties of the nervous system, has been a significant part of his artwork. Three features stimulated his artistic development: (1) nervous systems as functioning networks, (2) sequences of neural impulses that operate within these networks, and (3) the interactions of nervous systems with external environments. This has resulted in three types of artworks: (1) artist’s books, (2) paintings with overlaid grids to suggest the neural networks as interfaces between inner experience and outer reality, and (3) interactive sound sculptures and installations that, when viewers move around the pieces, generate nerve impulse—like sounds or words and phrases related to a nervous system experiencing the external environment. This paper describes the development of this artwork.

Event-triggered protocol-based adaptive impulsive control for delayed chaotic neural networks.

This article focuses on the synchronization problem of delayed chaotic neural networks via adaptive impulsive control. An adaptive impulsive gain law in a discrete-time framework is designed. The delay is handled skillfully by using the Lyapunov-Razumikhin method. To improve the flexibility of impulsive control, an event-triggered impulsive strategy to determine when the impulsive instant happens is designed. Additionally, it is proved that the event-triggered impulsive sequence cannot result in the occurrence of Zeno behavior. Some criteria are derived to guarantee synchronization for delayed chaotic neural networks. Eventually, an illustrative example is presented to empirically validate the effectiveness of the suggested strategy.

Adaptive impulsive consensus of nonlinear multi-agent systems via a distributed self-triggered strategy

This article investigates the consensus problem of nonlinear leader-following multi-agent systems (MASs) via adaptive impulsive control. A distributed impulsive controller is employed, in which an adaptive updating law in the discrete-time setting is designed for the impulsive gain. Moreover, in order to reduce the communication cost, a distributed self-triggered strategy is proposed to determine when the impulsive instant occurs. Some criteria are derived to guarantee consensus of leader-following MASs based on Lyapunov stability theory and algebraic Riccati equation. It is proved that the self-triggered impulsive sequence does not exhibit Zeno behaviour. Finally, an illustrative example is presented to empirically validate the effectiveness of the theoretical results.

Bounded impulse-control hovering formation in elliptical orbits

Satellite formation plays an important role in space missions such as on-orbit services and distributed space facilities. In these missions, hovering in a bounded range is one of the core tasks, but hovering technologies for the chief satellite in an elliptical orbit have been rarely investigated. Given the boundary constraints of relative motion between the chief and deputy satellites, this paper proposes two models for the design and control of hovering formation near an elliptical reference orbit through impulse: (1) the revisiting hovering formation model, which forces the deputy satellite to revisit the same relative position and maintains the formation via impulses; (2) the sequential-impulse-control hovering formation model, which uses a sequence of impulses to ensure the deputy satellite flies within the given boundary. Unlike the revisiting hovering formation model, this model does not require a fixed revisiting point, so the satellite’s trajectory is more flexible. The geometrical properties, formation maintenance strategy, and impulse-control solution for both models are investigated in detail. Finally, numerical simulations are conducted to verify the advantages of the proposed methods over other conventional methods, suggesting their wide applications in practical space missions.

Exploring the surge current degradation of natural ester oil-based nanofluids

The surge endurance of natural ester oil-based nanofluids against surge events is investigated experimentally. The focus of this work is the examination, through dielectric spectroscopy measurements, of the alteration of the real and imaginary parts of the complex relative permittivity of iron oxide nanofluids as a result of an accelerated degradation test employing a sequence of repetitive current impulses produced via a 12 kV/6 kA combination wave generator. The target is the exploration of a possible implementation of nanofluids as multipurpose liquids that act, in addition to insulation and coolants, as surge absorption media. Promising experimental results are discussed and compared with those of mineral oil that is widely used as a conventional insulating liquid in power transformers.

Numerical Analysis of the Wing Leading Edge Electro-Impulse De-Icing Process Based on Cohesive Zone Model

Aircraft icing has historically been a critical cause of airplane crashes. The electro-impulse de-icing system has a wide range of applications in aircraft de-icing due to its lightweight design, low energy consumption, high efficiency, and other advantages. However, there has been little study into accurate wing electric-impulse de-icing simulation methods and the parameters impacting de-icing efficacy. Based on the damage mechanics principle and considering the influence mechanisms of interface debonding and ice fracture on ice shedding, this paper establishes a more accurate numerical model of wing electric-impulse de-icing using the Cohesive Zone Model (CZM). It simulates the process of electric-impulse de-icing at the leading edge of the NACA 0012 wing. The numerical results are compared to the experimental results, revealing that the constructed wing electro-impulse de-icing numerical model is superior. Lastly, the effects of varying ice–skin interface shear adhesion strengths, doubler loading positions, and impulse sequences on de-icing effectiveness were studied. The de-icing rate is a quantitative description of the electro-impulse’s de-icing action, defined in the numerical model as the ratio of cohesive element deletions to the total elements at the ice–skin interface. The findings reveal that varying shear adhesion strengths at the ice–skin interface significantly impact the de-icing effect. The de-icing rate steadily falls with increasing shear adhesion strength, from 66% to 56%. When two, four, and seven impulses were applied to doubler two, the de-icing rates were 59%, 71%, and 71%, respectively, significantly increasing the de-icing efficiency compared to when impulses were applied to doubler one. Doubler one and two impulse responses are overlaid differently depending on the impulse sequences, resulting in varying de-icing rates. When the impulse sequence is 20 ms, the superposition results are optimal, and the de-icing rate reaches 100%. These studies can guide the development and implementation of a wing electric-impulse de-icing system.

Effects of impulse on prescribed-time synchronization of switching complex networks

The specified convergence time, designated by the user, is highly attractive for many high-demand applications such as industrial robot control, missile guidance, and autonomous vehicles. For the application of neural networks in the field of secure communication and power systems, the importance of prescribed-time synchronization(PTs) and stable performance of the system is more prominent. This paper introduces a prescribed-time controller without the fractional power function and sign function, which can reach synchronization at a prescribed time and greatly reduce the chattering phenomenon of neural networks. Additionally, by constructing synchronizing/desynchronizing impulse sequences, the PTs of switching complex networks(SCN) is achieved with impulse effects, where the time sequences of switching and impulse occurrences in the networks are constrained by the average dwell time. This approach effectively reduces the impact of frequent mode switching on network synchronization, and the synchronization time can be flexibly adjusted within any physically allowable range to accommodate different application requirements. Finally, the effectiveness of the proposed control strategy is demonstrated by two examples.

Finite-time lag synchronization for two-layer complex networks with impulsive effects

<abstract><p>This paper mainly considered the finite-time lag synchronization for two-layer complex networks with impulsive effects. Different types of controllers were designed to achieve the lag synchronization of two-layer complex networks. Several sufficient conditions on lag synchronization in the sense of finite time were derived. The time for synchronization was also estimated. It is important to note that synchronization time was influenced by the initial value, as well as the impulses and impulse sequence. This implied that different impulse effects result in varying synchronization times. Additionally, desynchronizing impulses can extend the synchronization time, whereas synchronizing impulses have the opposite effect. Finally, a numerical example was presented to showcase the practicality and validity of the proposed theoretical criteria.</p></abstract>

Asymptotic stability of fractional-order Hopfield neural networks with event-triggered delayed impulses and switching effects

This paper examines the asymptotic stability of nonlinear fractional-order switched systems (FOSSs) under a mode-dependent event-triggered delayed impulsive mechanism (MDETDIM). The impulses and switched signals are asynchronous. A novel MDETDIM is proposed to determine the impulsive sequence, which can prevent the Zeno phenomenon. Lyapunov-based asymptotic stability conditions for general FOSSs are derived using the proposed MDETDIM. The theoretical results are then applied to a fractional-order Hopfield neural network (FOHNN) with event-based delayed impulses and switching effects. Two examples are provided to demonstrate the effectiveness of our proposed results.

Stability analysis of nonlinear systems in the presence of event‐triggered impulsive control

AbstractThis note puts forward continuous event‐triggered impulsive control (CETIC) and dynamic event‐triggered impulsive control (DETIC) to discuss a class of (integral) input‐to‐state stability (iISS, ISS) for nonlinear systems (NSs), where the impulse sequences are produced by certain predesigned event‐triggering conditions. Different from traditionary event‐triggered control (ETC), CETIC indicates that a controller will be stimulated only if the given state‐dependent event condition is invoked. There exist no transfer of control between two continuous impulse triggered instants. Compared with the traditional static ETC, the DETIC can efficaciously lessen controller update and dramatically save energy at the same decay rate. In addition, all sample path solutions (SPS) for the system have the lowest time between events guaranteed to be positive. Utilizing CETIC strategy, we get some Lyapunov conditions to effectually avoid infinite triggering behavior and obtain the ISS‐type stability of the investigative systems. Then, one applies the theoretical consequences to NSs and derive a class of ETC mechanism with impulsive control gains (ICG) by linear matrix inequalities (LMIs). Because of the existence of timer, the DETIC strategy naturally excludes Zeno phenomena. Furthermore, conclusions in this thesis permit the upper bound estimation for the differential Lyapunov function coefficient to be time‐varying function instead of a constant in certain extant results, which means the criteria of the Lyapunov technique in this paper is less conservative and looser. Eventually, three examples with related simulations are demonstrated to indicate the rationalization and usefulness of our conclusion.

Fixed-time synchronization of delayed inertial Cohen–Grossberg neural networks with desynchronizing impulses

This article focuses on achieving fixed-time (FXT) synchronization of inertial Cohen–Grossberg neural networks (ICGNNs) in the presence of time-varying delays and desynchronizing impulsive effects. Firstly, a new lemma is presented to achieve FXT stability of the impulsive systems with destabilizing impulses. The settling-time function is shown to depend on both the parameters of impulsive sequence and continuous-time subsystems. Furthermore, based on the proposed lemma, sufficient conditions are established to achieve FXT synchronization of ICGNNS with desynchronizing impulses by designing a unified controller. Two numerical examples are taken into consideration to verify the efficacy of the proposed theoretical results.

Моделювання коливальних процесів віброударних систем

In order to improve the efficiency of methods and means of mathematical modeling of vibro-impact systems, a generalized function of the periodic mode of movement of the executive body has been developed. It is presented in the form of the dependence of the shock impulse on the ratio of the angular velocities of the linear conservative system and its own. When obtaining this function, the Heaviside integral jump function and the periodic Green's function were used. The function of the dependence of the oscillation frequency on the impact impulse is determined from the impact conditions for the function of the system's response to a periodic sequence of impulses. The design model of a vibroimpact system is considered, both with one impact element and a motion limiter, and with a double-sided impact pair with alternate impact interactions with the limiters. In the intervals between impacts, there is a linear force interaction. When developing the mathematical model, a stereomechanical impact model was used, which is characterized by the velocity recovery coefficient after the impact. The analysis of the dependence function of the oscillation frequency on the shock impulse made it possible to obtain skeletal diagrams of resonant and quasi-resonant oscillations of vibro-impact systems with one and many degrees of freedom. Based on the obtained phase diagrams of the state of vibro-impact systems, it was determined: in a system with a gap, an increase in the impact speed increases the oscillation frequency, and the vibro-impact nonlinearity is «hard»; in a system with tension, with an increase in the value of the shock impulse, the oscillation frequency decreases (nonlinearity is «soft»). In the absence of a gap, the system is isochronous. Depending on the initial energy reserve and the location of the limiters in an asymmetric oscillatory system, with one degree of freedom, there can be vibro-impact modes with both one (closer located) and both limiters. In a linear conservative system with several degrees of freedom, a single-impact T-periodic regime is realized. If the dissipation during motion and impact is very small, then a regime close to resonant can exist in the system. In this case, periodic oscillations are supported by a weak external periodic force. The developed mathematical model makes it possible to fully describe the process of changing the relative coordinate of the movement of the working body, both in transient and in the established modes of movement of the system.

Mean square exponential stabilization analysis of stochastic neural networks with saturated impulsive input

The exponential stabilization of stochastic neural networks in mean square sense with saturated impulsive input is investigated in this paper. Firstly, the saturated term is handled by polyhedral representation method. When the impulsive sequence is determined by average impulsive interval, impulsive density and mode-dependent impulsive density, the sufficient conditions for stability are proposed, respectively. Then, the ellipsoid and the polyhedron are used to estimate the attractive domain, respectively. By transforming the estimation of the attractive domain into a convex optimization problem, a relatively optimum domain of attraction is obtained. Finally, a three-dimensional continuous time Hopfield neural network example is provided to illustrate the effectiveness and rationality of our proposed theoretical results.

A Survey Paper on Arrhythmia Classification Using ECG Signals

Cardiovascular diseases (CVDs) rank among diseasesof highest mortality. Electrocardiography (ECG) is a non-invasive tool to assess the generalcardiac condition of a patient and is therefore as first-in-line examination for diagnosis of CVD.Arrhythmia Classification plays a major role while diagnosing heart diseases. Any change in the regular sequence of electric impulses is called as arrhythmia. Identifyingarrhythmia as early as possible helps the patient in choosing appropriate treatment. Classification of ECG arrhythmia with high accuracy is a challenging problem. Arrhythmiaclassification requires Acquisition of ECG signal, preprocessing ECG Signal, extraction of features, and optimization of the features and classification of arrhythmia. This paper presents survey on ECG denoising, feature extraction, optimization and classification. Furthermore, methods used to analyze the performance are also discussed. Limitations and drawbacks involved in ECG denoising, Feature Extraction and Classification are discussed concluding remarks and future scope. Keywords— ECG signal, Denoising, Feature Extraction, Arrhythmia Classification.

Event-triggered impulsive control for multi-agent systems with actuation delay and continuous/periodic sampling

The paper explores the event-triggered impulsive control for consensus problems in multi-agent systems (MASs) with actuation delay. Two types of event-triggered delayed impulsive control (ETDIC) schemes, predicated on continuous and periodic sampling, are proposed respectively. Several exponential consensus criteria for MASs are derived by using Lyapunov method. A correlation function is established between event parameters, actuation delay, and control strength to promote the co-design of the event-triggering policy and impulsive controller. It is shown that under the proposed ETDIC schemes, the interaction between neighboring agents is executed discontinuously, the upper bound information on the interval of two consecutive event impulses is not directly required. This results in reduced resource consumption of communication and control actions, as well as enhancing flexibility of the generated sequences of event impulses. Moreover, two representative examples with simulation results are given to illustrate the theoretical results.