Cascade Form Research Articles

Multiasset financial bubbles in an agent-based model with noise traders' herding described by an n -vector ising model

We present an agent-based model (ABM) of a financial market with $n>1$ risky assets, whose price dynamics result from the interaction between rational fundamentalists and trend-following imitative noise traders. The interactions and opinion formation of the noise traders are described by an extended $O(n)$ vector model, which generalizes the Ising model used previously in ABMs with a single risky asset. Efficient rejection-free transition probabilities are derived to describe realistic investment decisions at the microlevel of individual noise traders. The ABM is validated by testing for several characteristics of financial markets such as volatility clustering and fat tails of the distribution of returns. Furthermore, the model is able to account for the development of endogenous bubbles and crashes. We distinguish three different regimes depending on the traders' propensity to imitate others. In the subcritical regime of the $O(n)$ vector model, the traders' opinions are idiosyncratic and no bubbles emerge. Around the critical value of the $O(n)$ vector model, cross-sectionally asynchronous bubbles emerge. Above the critical value, small random price fluctuations may be amplified by noise traders herding into a given asset, which then impels fundamentalists to reequilibrate their more valuable portfolios that have become unbalanced, thus pushing the prices of the other assets upward. The resulting transient increase of the momenta of these assets triggers a reorientation of the noise traders' portfolios that further amplifies the burgeoning bubbles. We have thus identified a mechanism by which the cautious risk-adverse contrarian rebalancing strategy of fundamentalists leads to systemic risks in the form of cascades of bubbles spreading the whole financial market.

Controllability results for cascade systems of m coupled N-dimensional stokes and Navier-stokes systems by N – 1 scalar controls

In this paper we deal with the controllability properties of a system of m coupled Stokes systems or m coupled Navier-Stokes systems. We show the null-controllability of such systems in the case where the coupling is in a cascade form and when the control acts only on one of the systems. Moreover, we impose that this control has a vanishing component so that we control a m × N state (corresponding to the velocities of the fluids) by N — 1 distributed scalar controls. The proof of the controllability of the coupled Stokes systems is based on a Carleman estimate for the adjoint system. The local null-controllability of the coupled Navier-Stokes systems is then obtained by means of the source term method and a Banach fixed point.

Strong Stabilization of the Acrobot at the Down–Up Equilibrium Point⋆

In this paper, the strong stabilization of the Acrobot at the Down-Up equilibrium point is addressed, with the first link being downward and the second link being upright. By converting the strong stabilization of the Acrobot at the Down–Up equilibrium point equivalently to the existence and design of a stable stabilizing controller for a fourth-order single-input single-output linear plant with adjustable zeros, a pair of poles on the imaginary axis, and a pair of real poles located symmetrically with respect to the origin, this paper has three main contributions. Firstly, the existence of a stable stabilizing controller for any Acrobot which is linearly controllable at the Down–Up equilibrium point is proved by showing the range of the adjustable zero via adjusting a parameter of the output signal. Secondly, a necessary and sufficient condition on the mechanical parameters of the Acrobot is provided to guarantee the existence of a second-order stable stabilizing controller for the Acrobot around its Down– Up equilibrium point. Thirdly, a direct method is presented to design a second-order stable controller, whose transfer function is preset with three parameters. By utilizing the Liénard– Chipart criterion for a fourth-order polynomial, the necessary and sufficient conditions on these parameters for achieving the strong stabilization are obtained, which are expressed in a cascade form for obtaining these parameters conveniently. A numerical example is presented to validate the effectiveness of the proposed method.

Hybrid Active Flux Observer to Suppress Position Estimation Error for Sensorless IPMSM Drives

Harmonics and drifts are found in the position estimation errors of high-frequency signal injection (HFI) methods. To suppress the position estimation error, a hybrid active flux observer with disturbance rejection for both HFI method and model-based method is proposed. It fuses the position information from traditional HFI method and model-based method as the input of a disturbance observer, the estimated disturbance output can compensate measurement error for the two methods. Then a reduced-order natural speed observer is connected in a cascaded form to reject motor mechanical disturbance by estimating the load torque. Besides, a stator resistance identification algorithm is proposed, which is proved stable near zero frequency under persistent excitation condition. A tuning guideline for the whole algorithm is elaborated based on a rigorous stability analysis. Effective experiments and simulations verify the feasibility of the proposed scheme on a 0.75-kW interior permanent magnet synchronous motor drive platform.

Dynamic flame temperature tomography utilizing multi-camera common optical path

In the single projection direction, we propose a multi-camera common optical path system for three-dimensional radiation thermometry of dynamic flame, which is realized in the form of prism cascade. Different cameras can focus on certain sections of the flame along the main optical axis synchronously and independently. The image recorded by each camera linearly consists of a focused flame section and other remaining sections with defocused state. On the basis of point spread function, the spatial object-image mapping relationship is established by convolution, and the tomography of flame sections is performed by deconvolution. Then, the flame temperature is reconstructed by use of Planck's Law. The effectiveness of proposed method is verified by experiments, which could characterize the spatiotemporal evolution of flame temperature. Furthermore, it is expected to be able to achieve compatible measurements with high spatial and high temporal resolution.

Silicon Photonics Sensors for Biophotonic Applications—A Review

In the last two decades, biosensors have made a remarkable development in the area of food quality monitoring, drug discovery, environmental monitoring, soil quality monitoring, the healthcare industry, and medical point of care diagnosis. The integrated silicon photonic-based biosensors using the evanescent wave (EW) field and their advantages in terms of high sensitivity, high reliability, compactness, robustness, and miniaturization are discussed in this review. Specifically, different silicon photonic device configurations based on the EW field, such as interferometer-, resonator-, photonic crystal-, and Bragg grating-based biosensors, are discussed in detail. Moreover, various performance improvement strategies, such as advance and fundamental approaches, including Vernier effect-based systems in the cascaded form of the Mach–Zehnder interferometer (MZI)-ring resonator, are also reviewed. This article further reviews the usage of silicon-photonic biosensors for lab-on-chip (LOC) applications, including optoelectronic integrated circuits (OEICs). The state-of-the-art performance of different biosensors technologies is also comparatively discussed.

Spontaneous emergence of computation in network cascades

Neuronal network computation and computation by avalanche supporting networks are of interest to the fields of physics, computer science (computation theory as well as statistical or machine learning) and neuroscience. Here we show that computation of complex Boolean functions arises spontaneously in threshold networks as a function of connectivity and antagonism (inhibition), computed by logic automata (motifs) in the form of computational cascades. We explain the emergent inverse relationship between the computational complexity of the motifs and their rank-ordering by function probabilities due to motifs, and its relationship to symmetry in function space. We also show that the optimal fraction of inhibition observed here supports results in computational neuroscience, relating to optimal information processing.

The effects of dose, dose rate, and irradiation type and their equivalence on radiation-induced segregation in binary alloy systems via phase-field simulations

Radiation-induced segregation is a phenomenon commonly observed in many alloys which consists of the redistribution of elements (solute or interstitial impurities) under irradiation. The onset and development of radiation-induced segregation can only occur when a sufficient flux of defects is sustained and defect sinks are present. Irradiation dose, dose rate, and particle types all affect defect flux. In this work, we employ a phase-field model to examine the effects of dose, dose rate, and type of incident particles on radiation-induced segregation behavior in a model binary alloy. The phase-field model takes into account the formation and evolution of point defects as well as defect clusters, the diffusion and clustering of alloy species, the presence of additional extrinsic defect sinks in the form of dislocations, and two different methods of radiation-damage insertion, which are intended to simulate either light-ion/electron irradiation via Frenkel pairs or heavy-ion irradiation in the form of cascades. Our results show a dose-rate and particle-type dependence on the amount of solute segregation. We show that the material systems exposed to higher dose rates are less subjected to solute segregation at equivalent doses. We also show that such dose-rate-dependence behavior is due to a delay of the incubation dose at which radiation-induced segregation effectively starts. Particle type and the presence of dislocations can accentuate this behavior. Our model predictions correlate with many experimental observations made over the years on radiation-induced segregation providing credence to the simulation results. The methodology presented in this study allows for a first-order prediction of the dose rate at which proxy irradiation experiments could be performed to approximate radiation-induced segregation behaviors seen in targeted irradiation conditions.

Dynamic surface control with a nonlinear disturbance observer for multi‐degree of freedom underactuated mechanical systems

AbstractUnderactuated systems are extensively utilized in practice while attracting a huge deal of attention in theoretical studies. There are few robust control strategies for general underactuated systems because of the variety of their dynamic models. A dynamic surface control strategy with a nonlinear disturbance observer is proposed in this study, to stabilize multi‐degree of freedom underactuated systems. In such systems the number of underactuated degrees of freedom is not higher compared to the actuated ones. A disturbance observer is utilized to dispose of the uncertain disturbance and cross terms in dynamic model which may cause failure to the controller. Then, a dynamic surface control strategy is presented which is not sensitive to the diversity of dynamic models. The stability of whole system is proven by Lyapunov‐based method. The control law is successfully applied to nonlinear underactuated systems in benchmark cascade form such as two‐translational oscillator with rotational actuator, crane, wheeled inverted pendulum. The effectiveness of proposed controllers are illustrated by MATLAB simulation results. Finally, comparative studies are presented to verify the superiority of the proposed method.

Synthesis of dielectric-loaded waveguide filters as an inverse problem

ABSTRACT A design strategy is proposed for microwave devices built with dielectric-loaded waveguides having one- or two-dimensional discontinuity profiles. The problem is formulated as an inverse problem where the pre-defined scattering parameters are aimed to be the final response of the system. This goal is achieved by optimizing the dimensions of the filling materials. To increase the success of the optimization, the problem is reduced to the longitudinal and widthwise thickness determination of the unit cell, which constitutes the whole structure in a cascade form. To this aim, the frequency response of the unit cell is targeted and then that of the whole system, which is achieved by a two-level optimization procedure of the unit cell. The usefulness of the proposed design strategy is shown through numerical examples as well as the measurement results of two prototypes.

System Identification and Heuristic Control of Segmented Ailerons for Enhanced Stability of Fixed Wing UAVs

Different from conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed wing unmanned aerial vehicle (UAV) with a multi-segment ailerons. The multi-segment aileron setup is configured as a multi-input and single-output system and each segment is modeled as a control input. Experiments are conducted in a wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multi-segment ailerons perform as a single-segment aileron in a normal flight condition, and adapts to multi-segment control when encountering severe turbulence or a large angle reference change. Experimental results reveal that although each control surface has the capability for stabilization of the aircraft, the proposed control strategy by combining the multiple actuation surfaces reduces the mean squared errors for the roll angle up to $37$ percent in the highly turbulent environment providing superior disturbance rejection properties to the aircraft.

Active Disturbance Rejection Control for Uncertain Nonlinear Systems With Sporadic Measurements

This paper deals with the problem of active disturbance rejection control (ADRC) design for a class of uncertain nonlinear systems with sporadic measurements. A novel extended state observer (ESO) is designed in a cascade form consisting of a continuous time estimator, a continuous observation error predictor, and a reset compensator. The proposed ESO estimates not only the system state but also the total uncertainty, which may include the effects of the external perturbation, the parametric uncertainty, and the unknown nonlinear dynamics. Such a reset compensator, whose state is reset to zero whenever a new measurement arrives, is used to calibrate the predictor. Due to the cascade structure, the resulting error dynamics system is presented in a non-hybrid form, and accordingly, analyzed in a general sampled-data system framework. Based on the output of the ESO, a continuous ADRC law is then developed. The convergence of the resulting closed-loop system is proved under given conditions. Two numerical simulations demonstrate the effectiveness of the proposed control method.

Transmission characteristics of terahertz Bessel vortex beams through a multi-layered anisotropic magnetized plasma slab

The transmission of terahertz (THz) Bessel vortex beams through a multi-layered anisotropic magnetized plasma slab is investigated by using a hybrid method of cylindrical vector wave functions (CVWFs) and Fourier transform. On the basis of the electromagnetic boundary conditions on each interface, a cascade form of expansion coefficients of the reflected and transmitted fields is obtained. Taking a double Gaussian distribution of the plasma density as an example, the influences of the applied magnetic field, the incident angle and polarization mode of the incident beams on the magnitude, OAM mode and polarization of the transmitted beams are analyzed in detail. The results indicate that the applied magnetic field has a major effect upon the polarization state of the transmitted fields but not upon the transmitted OAM spectrum. The incident angle has a powerful influence upon both the amplitude profile and the OAM spectrum of the transmitted beam. Furthermore, for multiple coaxial vortex beams, an increase of the maximum value of the plasma density causes more remarkable distortion of both the profile and OAM spectrum of the transmitted beam. This research makes a stable foundation for the THz OAM multiplexing/demultiplexing technology in a magnetized plasma environment.

Modulation Method and Research of Vienna Rectifier in Hybrid Rectifier

With the development of modern industry becoming more intelligent, in the research field of power electronic devices, the demand for its comprehensive performance has further increased. Thus, the hybrid rectifier came into being. Hybrid rectification technology means that the controller controls two rectification devices connected in parallel with different structures to realize the conversion function. Among them, there is the most extensive research on a type of hybrid rectifier, with many variations. The circuit structure consists of two rectifiers connected in parallel with different structures. One part adopts a three-phase controllable rectifier structure, the other part adopts a diode uncontrolled rectifier bridge and a single power tube cascade form. We call the two parts rectifier A and rectifier B.

An Extension of Adaptive State Observers Using Dynamic Regressor Extension and Mixing With Relaxed Excitation Conditions

The recently proposed DREM-based adaptive state observer (DREMBAO) design approach assumes that there exists transformation of the system model into a cascade form, linearly dependent on parameters vector and depends only on measured input and output. This paper proposes an extension to relax that assumption and extend the approach to state affine systems. Like the original version of DREMBAO, the proposed approach ensures global convergence of an estimation error to zero under a relatively weak condition. The advantages of the extension are demonstrated in the example with a permanent magnet synchronous motor. In contrast to the original approach, the proposed extension allows taking into account viscous friction in the motor and obtaining a simplified load torque estimation algorithm. Moreover, finite-time convergence to zero is ensured for the load torque and speed estimation error under a weak interval excitation.

Data-Driven Backstepping Sliding-Mode Control of Disturbed QUAVs

Suffering from consistent external disturbances and unavailable kinetic dynamics, a data-driven backstepping sliding-mode control (DBSMC) scheme by the combination of backstepping technique and data-driven sliding-mode control is innovatively proposed for complex quadrotor unmanned aerial vehicles (QUAVs). To maintain the salient advantages of traditional PID algorithm, a data-driven PD-type sliding-mode surface is first designed for attitude subsystem, and thereby contributing to an efficient PD control law while with strong robustness and model-independent property. Then, the virtual control strategy and backstepping technique are further incorporated into the position controller design. In light of the virtual control philosophy, the proposed attitude controller and position controller are efficiently cohered in a cascade form, and the closed-loop stability pertaining to the DBSMC scheme can be ensured theoretically. Eventually, the effectiveness of the devised DBSMC scheme is evaluated via simulation studies.

Distributed Backward Pumped Raman Amplifiers Gain without Attenuation: A New Approach

Optical amplifiers have made a great achievement and a huge revolution in the world of optical communications, but some of the shortcomings must be occurs, for example, backward pump Raman amplifier suffers from decrease in gain. The main objective of this paper is to solve the problem of decrease that occurs in gain of backward pumped Raman amplifier. To solve this problem, we design a model of two of backward pumped Raman amplifiers are used in a cascaded form to overcome the attenuation in gain. We present the results in the case of using one backward pumped Raman amplifier compared to the model that we designed to show the difference between the two cases. Three types of fibers with different gain parameters are used. We also simulate and analyze the parameters that affect the Raman gain of fiber Raman amplifier for three different types of fiber. The gain depends heavily on the length of the fiber and the pumping power, according.

Towards a Reliable and Sensitive Deep Learning Based Approach for Multi-Ship Detection in SAR Imagery

Synthetic Aperture Radar (SAR) images show promising results in monitoring maritime activities. Recently, Deep learning-based object detection techniques have impressive results in most detection applications but unfortunately there are challenging problems such as difficulty of detecting multiple ships, especially inshore ones. In this paper, a three-step ship detection process is described and a reliable and sensitive hybrid deep learning model is proposed as an efficient classifier in the middle step. The proposed model combines the finetuned Inception-Resnet-V2 model and the Long Short Term Memory model in two different approaches: parallel approach and cascaded approach. In experiments, the region proposal algorithm and the Non-Maxima suppression algorithm are applied in the first and last step in the three-step detection process. The comparative results show that the proposed approach in cascaded form outperforms the competitive recent state-of-the-art approaches by enhancement up to 16.3%, 16.5%, and 18.9% in terms of recall, precision and mean average precision, respectively. Moreover, the proposed approach shows high relative sensitivity for challenged cases of both inshore and offshore scenes by enhancement ratios up to 81.88% and 24.58%, respectively in recall perspective.

Deconstructing scale-free neuronal avalanches: behavioral transitions and neuronal response

Observations of neurons in a resting brain and neurons in cultures often display spontaneous scale-free (SF) collective dynamics in the form of information cascades, also called ‘neuronal avalanches’. This has motivated the so called critical brain hypothesis which posits that the brain is self-tuned to a critical point or regime, separating exponentially-growing dynamics from quiescent states, to achieve optimality. Yet, how such optimality of information transmission is related to behavior and whether it persists under behavioral transitions has remained a fundamental knowledge gap. Here, we aim to tackle this challenge by studying behavioral transitions in mice using two-photon calcium imaging of the retrosplenial cortex (RSC)—an area of the brain well positioned to integrate sensory, mnemonic, and cognitive information by virtue of its strong connectivity with the hippocampus, medial prefrontal cortex, and primary sensory cortices. Our work shows that the response of the underlying neural population to behavioral transitions can vary significantly between different sub-populations such that one needs to take the structural and functional network properties of these sub-populations into account to understand the properties at the total population level. Specifically, we show that the RSC contains at least one sub-population capable of switching between two different SF regimes, indicating an intricate relationship between behavior and the optimality of neuronal response at the subgroup level. This asks for a potential reinterpretation of the emergence of self-organized criticality in neuronal systems.

Hysteresis in Supersonic Flow Past a Plane Cascade of Cylindrical Rods

—The results of numerical simulation of the interaction of supersonic flow with a permeable screen in form of an infinite plane cascade (lattice) of circular cylinders are given. The interaction regime in which the shocks ahead of the cylinders are localized on the scale of the cascade step is considered. The multi-block computational technique in which the viscous boundary layers are resolved by means of local grids using the Navier–Stokes equations, while the effects of inteferrence between the shock-wave structures in supersonic wake are described within the framework of Euler’s equations. The action of shock waves induced by the neighboring elements of lattice to the near-wake region behind the intermediate elements can ambiguously affect the aerodynamic lattice performance as well as generate time-dependent phenomena in the wake. The flow regimes are classified depending on continuous increase and decrease in the free-stream supersonic air flow in the Mach number range from 2.4 to 4.2 with reference to the lattice of the 80% permeability. The sources of the hysteresis behavior of the lattice aerodynamic drag with respect to the Mach number and the mechanisms of the onset of self-oscillating wake flow regimes are discussed.