Impulsive Disturbances Research Articles

A method for signal components identification in acoustic signal with non-Gaussian background noise using clustering of data in time-frequency domain

This paper presents a novel method for fault detection in vibration/acoustic signals contaminated with non-Gaussian noise, specifically addressing the challenge of random impulsive and wideband disturbances in industrial measurements. While damage detection in Gaussian noise environments is well understood, high-amplitude non-cyclic impulsive disturbances arising from random aspects of industrial processes, such as non-uniform operations and random impacts, pose significant analytical challenges.The proposed method analyzes the distribution densities of spectral vectors derived from spectrograms. It considers a simple additive model consisting of the signal of interest (SOI) and Gaussian and non-Gaussian noise. Using the density-based spatial clustering algorithm (DBSCAN), the method isolates distinct classes of spectral vectors from the spectrogram, effectively separating different signal behaviors and extracting fault-related information. The effectiveness of the proposed method was validated using an envelope spectrum-based indicator (ENVSI) and successfully demonstrated on real signals from an industrial machine with a faulty bearing.

Dopamine agonists in the treatment of Parkinson's disease: the show must go on.

Dopamine agonists (DA) have proven very successful in the treatment of Parkinson's disease for a good many years now. In the 1990's they experienced a high level of acceptance particularly in the European countries because their efficacy was in fact established, their tolerability was improved on and, in addition, several preparations were available with longer effect durations. But the discovery of cardiac fibroses led to a substantial setback and even rejection of therapy using ergoline DA. In recent years, impulse control disturbances have been observed increasingly with the result that higher doses have been reduced and the previously popular use of non-ergoline DA was discontinued. In addition, newer data on levodopa were published which clearly relativized the occurrence of late complications under levodopa and led to a differentiated use. Thus the importance of their use has waned over the years. But we should rather avoid repeating the mistakes of the past. DA serve us well and reliably so. The pendulum apparently thrives of the extremes but in the case of DA we should keep from falling back into the other extreme: We can and in fact must further make use of the DA, but with a clear view of specific goals and in a differentiated way. DA constitute the second-most important substance class after levodopa. Their optimized application can only be recommended for the good of our patients.

Combined-Step-Size Affine Projection Andrew’s Sine Estimate for Robust Adaptive Filtering

Recently, an affine-projection-like M-estimate (APLM) algorithm has gained popularity for its ability to effectively handle impulsive background disturbances. Nevertheless, the APLM algorithm’s performance is negatively affected by steady-state misalignment. To address this issue while maintaining equivalent computational complexity, a robust cost function based on the Andrew’s sine estimator (ASE) is introduced and a corresponding affine-projection Andrew’s sine estimator (APASE) algorithm is proposed in this paper. To further enhance the tracking capability and accelerate the convergence rate, we develop the combined-step-size APASE (CSS-APASE) algorithm using a combination of two different step sizes. A series of simulation studies are conducted in system identification and echo cancellation scenarios, which confirms that the proposed algorithms can attain reduced misalignment compared to other currently available algorithms in cases of impulsive noise. Meanwhile, we also establish a bound on the learning rate to ensure the stability of the proposed algorithms.

Effects of cognitive training and behavior modification on aggressive behavior and sleep quality in schizophrenia.

Schizophrenia (SCZ) is linked to a heightened risk of impulsive aggression and disturbances in sleep patterns. Cognitive and social cognitive impairments have been connected to aggression, with social cognitive deficits appearing to play a more immediate role. In this investigation, we conducted a retrospective analysis of the impact of cognitive training and sleep interventions on aggressive behavior and the quality of sleep among individuals with SCZ who were hospitalized. This study divided 80 hospitalized patients into two groups according to medical advice, namely the normal group and the study group. The control group received routine drug treatment and education; The research group implemented cognitive training and sleep intervention based on the normal group. Collect basic clinical data, aggressive behavior indicators, and sleep quality indicators. There is no difference in the basic information statistics between the two groups. Both groups can reduce aggressive behavior and improve sleep quality. In the study group, there was a notable decrease in aggressive behavior compared to the control group. Furthermore, the sleep quality in the study group exhibited significant improvement when compared to the control group. Cognitive training and sleep intervention have been proven to be effective nonpharmacological treatments, effectively reducing aggressive behavior and improving sleep quality.

Improving the insulin therapy for diabetic patients using optimal impulsive disturbance rejection: Continuous time approach

The paper proposes a new model-based optimization approach to improve the clinical efficiency of compensatory insulin bolus treatment in diabetic patients, aiming to mitigate the consequences of diabetes. The most important contribution of this paper is a novel methodology for determining the optimal parameters of insulin treatment, namely the size and timing of insulin boluses, to effectively compensate for carbohydrate intake. This concept can be seen as the so-called optimal model-based bolus calculator. The presented theoretical framework deals with the problem of optimal disturbance rejection in impulsive systems by minimizing an integral quadratic cost function. The methodology considers a personalized empirical transfer function model with static gains and time constants as the only parameters assumed to be known, making the bolus calculator more straightforward to implement in clinical practice. Contrary to other techniques, the proposed methodology considers impulsive insulin administration in the form of boluses, which is more feasible than continuous infusion. In contrast to the conventional bolus calculator, the proposed algorithm allows for maximizing therapy performance by optimizing the relative time of insulin bolus administration with respect to carbohydrate intake. Another feature to highlight is that the solution of the optimization problem can be obtained analytically, hence no numerical iterative solvers are required. Additionally, the continuous-time domain approach allows for a much finer adjustments of the insulin administration timing compared to discrete-time models. The proposed approach was validated in an in-silico study, which demonstrated the importance of systematically determined insulin–carbohydrate ratio and the relative delay between disturbance and its compensation. The results showed that the proposed optimal bolus calculator outperforms the traditional suboptimal formula.

Temperature control of beer fermentation based on variable domain fuzzy PID and neural network technology and its application analysis

AbstractTemperature control in the beer manufacturing process is crucial for product quality. Given the gap between China's automation in beer production and the international level, improving the technology in this area has gradually become a core issue in optimizing domestic beer production. This study combines a proportional integral derivative controller with a fuzzy modeling strategy and incorporates a variable‐domain structure to propose a variable‐domain fuzzy proportional integral derivative controller control method. To cope with the challenges of production interaction, the study also introduces neural network technology. The experimental data indicated that the variable‐domain fuzzy proportional integral derivative controller outperforms the conventional proportional integral derivative controller and the fuzzy proportional integral differential controller in terms of overshooting, with a maximum overshoot of only 1.0, compared with 0.50 and 0.70, respectively. The variable‐domain fuzzy proportional integral differential controller exhibited a minimal overshoot of only 0.01 when the model parameter is increased by 20%. In comparison, the other methods reach overshoot values of 0.92 and 1.0. The proposed method maintained superior stability even under the influence of impulse disturbance, step disturbance, and modeling variations. These results demonstrated that the research method is significantly more stable than both the proportion integration differentiation (PID) controller and fuzzy PID controller in complex dynamic parameter environments. The proposed method involved 60 rounds of neural network control, which was successfully implemented. The temperature readings T1 and T2 remained stable within the range of 1.0%–1.02% throughout the experiments. The study demonstrates that the proposed methods have higher accuracy and less fluctuation in actual application, making them more available. Taken together, the above results show that the combination of variable‐domain fuzzy PID controller and neural network technology in beer production has achieved excellent control results. This study not only provides a strong technical support for the progress of beer production technology in China, but also has important industrial application value and wide promotion prospects.

Stability and Synchronization of Delayed Quaternion-Valued Neural Networks under Multi-Disturbances

This paper discusses a type of mixed-delay quaternion-valued neural networks (QVNNs) under impulsive and stochastic disturbances. The considered QVNNs model are treated as a whole, rather than as complex-valued neural networks (NNs) or four real-valued NNs. Using the vector Lyapunov function method, some criteria are provided for securing the mean-square exponential stability of the mixed-delay QVNNs under impulsive and stochastic disturbances. Furthermore, a type of chaotic QVNNs under stochastic and impulsive disturbances is considered using a previously established stability analysis method. After the completion of designing the linear feedback control law, some sufficient conditions are obtained using the vector Lyapunov function method for determining the mean-square exponential synchronization of drive–response systems. Finally, two examples are provided to demonstrate the correctness and feasibility of the main findings and one example is provided to validate the use of QVNNs for image associative memory.

Stabilization of nonlinear delayed systems subject to impulsive disturbance via aperiodic intermittent control

In this paper, the finite-time stabilization (FS) of nonlinear delayed systems subject to impulsive disturbance is addressed via designing an aperiodic intermittent control (APIC), which can be segmented into time-triggered intermittent control (TAPIC) and event-triggered intermittent control (EAPIC). On account of Lyapunov method, sufficient conditions are exhibited to render FS can be achieved. Under TAPIC, the relationship between impulsive disturbance and control parameters is set up, from which the impulsive instants and the width of each control period can be resolved. In the framework of finite-time stabilization, the relationship among impulsive disturbance, intermittent control parameters, threshold value of event-triggered mechanism (ETM) under EAPIC is built up to ensure FS, and the sequence of impulsive disturbance instants is generated by the pre-designed ETM. Besides, the Zeno phenomenon can be ruled out. Based on the Chua’s oscillator with time delay, two examples are depicted to demonstrate the validity of the acquired results under TAPIC and EAPIC, respectively.

An Overview Of The Level Of Occupational Stress Of Anesthesiologists In The Surgical Room Of The Hospital In The Banyumas District Area

Exercise can indeed improve the quality of health if it is done in accordance with the rules or program. However, excessive exercise without considering the capacity of the organs, especially the heart, can result in disease, one of which is heart disease, namely heart rhythm disturbances. The death rate for athletes in 2022 will still be at 29% during competition. In this case, it proves that Holter monitoring (ambulatory ECG monitoring) is better in assessing heart rhythm in athletes. Arrhythmias in athletes are caused by inadequate cardiac remodeling, causing ion channels in the atrioventricular node to undergo immunohistochemical labeling, where L-type calcium (Ca2+) channels that carry inward current are known to play a major role in the diastolic depolarization of the atrioventricular node, and regulate the excitability and increase in axis potentiation. . In the important Ca2+ channels in the heart, a slowing process occurs which results in a barrier to atrioventricular node conduction. A decrease in the axis action potential phase process where calcium cannot replace potassium in cells results in electrical impulse disturbances.

Intermittent control for stabilization of uncertain nonlinear systems via event-triggered mechanism

<p>This paper studies the finite-time stabilization (FTS) and finite-time contraction stabilization (FTCS) of parameter-uncertain systems subjected to impulsive disturbances by using an event-triggered aperiodic intermittent control (EAPIC) method, which combines aperiodic intermittent control with event-triggered control. By employing the Lyapunov method and linear matrix inequality techniques, sufficient conditions for FTS and FTCS are derived. Additionally, within the finite-time control framework, relationships among impulsive disturbance, intermittent control parameters, and event-triggered mechanism (ETM) thresholds are established under EAPIC to ensure FTS and FTCS. The sequence of impulsive moments is determined by a predetermined ETM, and Zeno phenomena are also excluded. Finally, the effectiveness of the EAPIC approach is demonstrated through two numerical examples.</p>

The preview control of a corticothalamic model with disturbance

<abstract><p>Based on a neural field network model with impulsive and random disturbances, a preview control method that makes full use of known future information is proposed to reduce the static error of the target signal and the transient oscillatory behavior of the controlled system when it receives random disturbance inputs. The preview controller for epileptic seizures is constructed, and the feasibility and effectiveness of clinical single-target and multi-target stimulation in epilepsy regulation are explored from a computational perspective. In addition, a performance index function is proposed to evaluate the energy consumption of controller with and without preview under different input (target) strategies. Suggestions for different strategies are given in terms of the individualized disease environment of patients. From the perspective of seizure control effectiveness and performance consumption, the results show that the preview controller has a greater advantage. The theory of preview control is applied to the control of epileptic seizures for the first time, and the conclusions of the multifaceted study provide some references for clinical trials and controller applications.</p></abstract>

Extreme Geomagnetic Disturbances (GMDs) Observed in Eastern Arctic Canada: Occurrence Characteristics and Solar Cycle Dependence

AbstractExtreme (>20 nT/s) geomagnetic disturbances (GMDs, also denoted as MPEs—magnetic perturbation events)—impulsive nighttime disturbances with time scale ∼5–10 min, have sufficient amplitude to cause bursts of geomagnetically induced currents (GICs) that can damage technical infrastructure. In this study, we present occurrence statistics for extreme GMD events from five stations in the MACCS and AUTUMNX magnetometer arrays in Arctic Canada at magnetic latitudes ranging from 65° to 75°. We report all large (≥6 nT/s) and extreme GMDs from these stations from 2011 through 2022 to analyze variations of GMD activity over a full solar cycle and compare them to those found in three earlier studies. GMD activity between 2011 and 2022 did not closely follow the sunspot cycle, but instead was lowest during its rising phase and maximum (2011–2014) and highest during the early declining phase (2015–2017). Most of these GMDs, especially the most extreme, were associated with high‐speed solar wind streams (Vsw >600 km/s) and steady solar wind pressure. All extreme GMDs occurred within 80 min after substorm onsets, but few within 5 min. Multistation data often revealed a poleward progression of GMDs, consistent with a tailward retreat of the magnetotail reconnection region. These observations indicate that extreme GIC hazard conditions can occur for a variety of solar wind drivers and geomagnetic conditions, not only for fast‐coronal mass ejection driven storms.

Identification of time-varying inertia tensor parameters of a space solar power satellite based on a robust weighted recursive algorithm under impulsive disturbance

Considering changes in the structural size and mass caused by the on-orbit assembly process in a planar space solar power satellite, this study proposes an improved robust recursive algorithm to identify the time-varying inertia tensor parameters of the system. In this algorithm, to decrease the effect of impulsive disturbance on inertial parameter identification during the on-orbit assembly and improve computational accuracy, robust weighted factor and multi-innovation theory are involved. Then, the time-varying inertia tensor parameters of this large flexible structure are identified based on the distributed measurement results of multiple attitude sensors. The simulation results indicate that the proposed algorithm improves the identification accuracy and has better robustness than the original method under the impulsive disturbance. The relative values of the average relative error caused by the impulsive disturbance under the proposed algorithm are approximately 27.8–73.0% less than those under the original method. Additionally, the results also demonstrate that the proposed algorithm has higher noise immunity than the classical recursive least-squares method in a time-varying system. When the impulsive disturbance and zero-mean Gaussian white noise are applied to the system, compared with the conventional recursive least-squares method, the proposed algorithm yields lower absolute and relative values of the average relative error by approximately 4.2% and 44.9%, respectively.

Nonlocal effect on shear wave propagation in a fiber-reinforced poroelastic layered structure subjected to interfacial impulsive disturbance

The present study illuminates the influence of impulsive line source on Horizontally polarized shear (SH) waves propagating in a stratified structure consisting of two distinct nonlocal fiber-reinforced layers with voids over a foundation with nonlocal functionally graded fiber-reinforced substrate with voids. The governing equations for a nonlocal fiber-reinforced poroelastic medium are established. The proposed mathematical model incorporates the Green’s function technique and the Fourier transformation to yield the complex dispersion relation of the propagating wave. The study discloses the existence of two wave fronts of SH-waves propagating with different speeds through the layered structure. The second wave front arises as a result of existence of void pores, while the first wave front defines SH-wave propagation in a nonlocal fiber-reinforced layered structure. Each wave front possesses individual critical frequency beyond which they fail to propagate. Speeds of both wave fronts are influenced by the appearance of nonlocality parameter. Using MATHEMATICA, several graphs have been plotted to demonstrate the impact of key parameters on the dispersion and attenuation of both wave fronts. Some notable cases have been derived which validate the present mathematical model.

Saturated control for uncertain nonlinear impulsive systems with non-uniformly distributed packet loss

This article aims to provide a unified theoretical framework for studying the dynamic behavior of uncertain impulsive systems involving saturation structure and packet loss phenomenon. The concept named average packet loss interval (APLI) is developed to characterize the distribution of packet loss intervals. In this scenario, the traditional restrictions on the number, the proportion, or the upper bound of packet loss intervals can be significantly relaxed. By modeling the original systems as the asynchronous impulsive switched systems, some sufficient criteria are derived via the set invariant approach, addressing how to integrate the effects of impulsive and external disturbances into input-to-state stability (ISS) performance. It is also shown that the robustness of system performance against packet loss can be guaranteed ideally. Then, an optimization algorithm is designed with the hope of getting the maximum estimate of the domain of initial values. Finally, two examples are discussed to demonstrate the effectiveness of our proposed results.

Tracking arbitrary free nutating trajectories of the Lagrange top using Floquet theory: linear feedback approach

We consider the problem of tracking arbitrary free nutating trajectories of the Lagrange top using linear feedback. The equations of motion of the top are linearised about the desired trajectories. Due to the inherent symmetries, this yields a system of linear equations with periodically varying coefficients governing the error dynamics. It is shown that the higher-order dynamics of the Lagrange top leads to nuances in the implementation of the control. Two different control strategies are implemented in the present work. These are applicable for impulsive and short-duration disturbances, respectively. The control effort is in the form of a body-fixed torque input about the symmetry axis and a vertical space-fixed force input. In both the proposed control strategies, the iterative application of the control effort over multiple periods is shown to stabilise the error. These strategies are shown to work for significantly large errors.

Stability of nonlinear impulsive systems with non-uniformly distributed packet loss

This study focuses mainly on the stability of a class of nonlinear systems with impulsive disturbance. In particular, we consider the possible non-uniformly distributed packet loss phenomenon in the controller-to-actuator channel. This packet loss is described by a characterization scenario in the average sense, known as the average packet loss interval (APLI). In this scenario, an average allocation strategy between the number of impulsive sampling intervals and the length of packet loss intervals is established. This implies that the limitations on the proportion or the upper bound of packet loss intervals can be relaxed. A sampled-data control is put forward based on impulsive disturbance, which not only brings better control performance but also reduces conservatism. In view of the Halanay inequality, the number of subsystem switchings caused by packet loss is allowed to be arbitrary. Based on the elastic constraint relationships established between system parameters and APLI, a series of conditions guaranteeing the globally uniformly exponential stability (GUES) are provided. Further, the admissible packet loss intervals can be estimated on an average basis by solving an algebraic inequality. Finally, a numerical example is discussed to demonstrate the validity of our study.

ω-Limit Sets of Impulsive Semigroups for Hyperbolic Equations

In this paper, we investigate the qualitative behavior of an evolutionary problem consisting of a hyperbolic dissipative equation whose trajectories undergo instantaneous impulsive discontinuities at the moments when the energy functional reaches a certain threshold value. The novelty of the current study is that we consider the case in which the entire infinite-dimensional phase vector undergoes an impulsive disturbance. This substantially broadens the existing results, which admit discontinuities for only a finite subset of phase coordinates. Under fairly general conditions on the system parameters, we prove that such a problem generates an impulsive dynamical system in the natural phase space, and its trajectories have nonempty compact ω-limit sets.

Technique for the comprehensive characterization of supraharmonic disturbances (9–150 kHz) in the joint time-frequency domain

The inverter-based devices connected to the low-voltage (LV) grid, such as photovoltaic panels (PVs) and electric vehicle charging stations (EVCSs), are known to generate supraharmonic distortions in CISPR Band A (9–150 kHz) that may interfere power line communications (PLC). Current measurement methods were designed to provide results of the disturbances only in the frequency domain. Thus, impulsive signals and fast amplitude variations of the disturbances are lost in the calculation process. This work addresses this issue by developing a statistical study of the distribution of supraharmonic disturbances in the joint time-frequency domain, which allows the clear differentiation of impulsive signals. The results show that the amplitudes of the normalized measurements can be modeled by the t Location-Scale probability density function (PDF), which can be used to set a threshold for the differentiation of the impulsive disturbances. The study proposes a measurement method and a set of metrics for the complete characterization of the disturbances present in the LV grid, by characterizing the noise and distortions as a whole and also impulsive emissions separately. The main contribution of this work is that the measurement technique characterizes the disturbances in the joint time-frequency domain, and it is coherent with methods below 9 kHz. The proposed method is applied to some typical grid recordings containing different types of noise and emissions. The results demonstrate that the method allows the complete characterization of the supraharmonic distortions present in the LV grid and a proper differentiation of the impulsive emissions in the joint time-frequency domain.

Lyapunov-based stability of time-triggered impulsive logical dynamic networks

In this paper, we consider the stability of impulsive logical dynamic systems (ILDNs) from two aspects: impulsive disturbance and impulsive control. The existing results on the stability of ILDNs only consider the stability of ILDNs under a given impulsive instant sequence (IIS), which has some limitations and motivates us to consider the stability of ILDNs under any IIS. By constructing a merged ILDN, under the assumption that the non-impulsive process and impulsive process are all globally stable, a necessary and sufficient condition on the stability of ILDNs under any IIS is proposed at first. Unfortunately, the obtained result is too restrictive, and in practice, it is not common that a stable LDN is still stable under any IIS. The fact is that for any stable LDN, there exist some IISs such that its stability is destroyed, and these IISs are called impulsive disturbances; for any unstable LDN, there exist some IISs such that the stability can be achieved, and these IISs are called impulsive control. To investigate the stability of ILDNs, the concept of average impulsive interval is first introduced to ILDNs, and several sufficient conditions are proposed to ensure the stability of LDNs under the time-triggered IISs with the property of average impulsive interval. Moreover, the obtained results are applied to the set stability of ILDNs.