Feedback Delay Research Articles

Engineering knowledge for medical applications

This paper describes and discusses the engineering knowledge, mainly production engineering knowledge, which is expected to be used for surgical support systems in the near future and beyond. With regard to artificial joint replacement, the paper discusses bone resection characteristics, focusing on the experimental results of cutting force and temperature rise. In addition, registration techniques, and measurement and resection accuracy are described. In the area of microsurgery, neurosurgery and ophthalmology are covered, and the introduction of AI is also introduced. In ophthalmology, the automation of peeling procedures is discussed. In remote surgery, experimental results on the relationship between force feedback and time delay, which is a crucial problem in remote surgery, are introduced. Furthermore, as future surgical support systems, the application of high intensity focused ultrasound (HIFU) and the use of microrobots are discussed. Finally, this paper describes the situations in which surgical robots are expected to play an active role.

Controlling nonlinearity and memory by feedback delay time in delay-based reservoir computing

Controlling nonlinearity and memory by feedback delay time in delay-based reservoir computing

AMIS-MU: Edge Computing Based Adaptive Video Streaming for Multiple Mobile Users

The increasing demand for online high-quality video streaming has brought huge challenges to the traditional client-server video streaming systems due to the high feedback delay, rigorous bandwidth requirement, and the lack of a mechanism of centralized resource management between users. In this work, we propose AMIS-MU, an edge computing-based mobile video streaming system that optimizes the watching experience of users via playback adaptation and channel resource allocation. AMIS-MU fully explores the power of edge servers from three perspectives. First, by pre-caching videos from the cloud, AMIS-MU analyzes video contents at the edge, and achieves a nearly imperceptible content-based playback speed adaptation. Second, as the edge server controls the channel resources of users in a centralized fashion, AMIS-MU adaptively updates the channel configuration to optimize the overall watching experience. Last, the plenty of computational power available at the edge enables a more intelligent playback control by using deep reinforcement learning (DRL). We propose a novel usage of DRL which significantly reduces the complexity of the cross-layer joint optimization problem and solve the non-convex channel resource allocation problem by Lyapunov optimization. Experiments show that AMIS-MU outperforms other existing algorithms in terms of average QoE and fairness.

Parkinsonian Tremor as Unstable Feedback in a Physiologically Consistent Control Framework.

Parkinson's disease (PD) is characterized by decreased dopamine in the basal ganglia that causes excessive tonic inhibition of the thalamus. This excessive inhibition seems to explain inhibitory motor symptoms in PD, but the source of tremor remains unclear. This paper investigates how neural inhibition may change the closed-loop characteristics of the human motor control system to determine how this established pathophysiology could produce tremor. The rate-coding model of neural signals suggests increased inhibition decreases signal amplitude, which could create a mismatch between the closed-loop dynamics and the internal models that overcome proprioceptive feedback delays. This paper aims to identify a candidate model structure with decreased-amplitude-induced tremor in PD that also agrees with previously recorded movements of healthy and cerebellar patients. The optimal feedback control theory of human motor control forms the basis of the model. Key additional elements include gating of undesired movements via the basal ganglia-thalamus-motor cortex circuit and the treatment of the efferent copy of the control input as a measurement in the state estimator. Simulations confirm the model's ability to capture tremor in PD and also demonstrate how disease progression could affect tremor and other motor symptoms, providing insight into the existence of tremor and non-tremor phenotypes. Altogether, the physiological underpinnings of the model structure and the agreement of model predictions with clinical observations provides support for the hypothesis that unstable feedback produces parkinsonian tremor. Consequently, these results also support the associated framework for the neuroanatomy of human motor control.

A delay-product-type Lyapunov functional approach for enhanced synchronization of chaotic Lur'e systems using a quantized controller

<abstract><p>The asymptotic synchronization problem of chaotic Lur'e systems in the master-slave framework was explored in this paper. A time-varying delay feedback controller with quantization considerations and a delay-product-type Lyapunov-Krasovskii functional technique were employed to tackle this problem. Consider an error system based on master and slave systems, for which sufficient asymptotic stability requirements are developed to assure that the addressed system achieves proper synchronization. Following that, the desired control gain was determined by finding a feasible solution to these stability requirements. The results of this paper were validated using a numerical example with simulations, which revealed that they were superior to previously published ones.</p></abstract>

Stabilization of hybrid stochastic differential equations by delay feedback control based on discrete-time observations

Stabilization of hybrid stochastic differential equations by delay feedback control based on discrete-time observations

Hardware fingerprint construction of optical transmitters based on permutation entropy spectrum of chaos for secure authentication

In this paper, an optical transmitter authentication method using hardware fingerprints based on the permutation entropy spectrum (PES) of electro-optic chaos is proposed. By means of permutation analysis of chaotic time series generated by the electro-optic feedback loop, PES is defined and used as the hardware fingerprint of optical transmitters for secure authentication. The time division multiplexing (TDM) module is used to combine the chaotic signal and the message, while the optical temporal encryption (OTE) module is introduced to ensure the security of the fingerprint. At the receiver, the time division demultiplexing (TDD) module and the optical time decryption (TDD) module are introduced to recover the original chaotic signal. The trained support vector machine (SVM) models will then recognize legal and illegal optical transmitters by judging whether the PES of the received chaotic signal is legitimate or not. The simulation and experimental results show that PES of electro-optic chaos has obvious fingerprint characteristics and is sensitive to the feedback delay T in the feedback loop. The authentication system based on PES can recognize both legal and illegal transmitters in optical networks, and the recognition accuracy can reach about 97%. Under the condition of a low signal-to-noise ratio, the authentication system based on the permutation entropy spectrum can still distinguish legal and illegal transmitters effectively. Meanwhile, our scheme has high controllability and flexibility.

Bifurcations of a fractional three-layer neural network with different delays: Delay-dependent and order-dependent

In this paper, a novel fractional three-layer delayed neural network is proposed, which is a generalization of some existing BP neural networks and has greater information acquiring ability and fault tolerance. First, the sum of the involved transmission delay and feedback delay is taken as the bifurcation parameter and some delay-induced Hopf bifurcation criteria is given based on the stability theorem of linear system and Hopf bifurcation theorem. Then, as an extension of the traditional delay-induced Hopf bifurcation, the order-induced Hopf bifurcation is further explored by combining implicit function array solution method. Finally, the application and validity of our presented theoretical results are illustrated by two numerical examples. Moreover, the impact of the time delays on the order-induced Hopf bifurcation is deeply discussed through computation and illustration. It is discovered that the critical value of the fractional order becomes smaller when the sum of the involved transmission delay and feedback delay increases.

Impact of extended warranty service on product pricing in online direct retailers' competitive market

In this paper, we consider a model composed of the three largest online direct retailers to investigate the impact of extended warranty service on product pricing. A single-period static game model and a dynamic game model with two delays are built. We discuss the optimal game strategies and dynamic evolution game behaviors of retailers and analyze the effects of warranty period and price adjustment speed on system stability. The result shows that the optimal extended warranty price, green degree, and extended warranty period lead to the biggest profits for the retailer. From the perspective of maximum profit, retailers should give priority to extending the warranty period, followed by extending the warranty price and extending the green degree of warranty. For the sake of system stability and player performance, retailers should take recent historical data as a reference, and a relatively slow price adjustment speed is needed. To better maintain the stability of the system, the delay feedback control method is adopted which can successfully control the instability of the system.

An area efficient vedic multiplier for FFT processor implementation using 4-2 compressor adder

ABSTRACT This article proposes a compact compressor adder of Vedic multiplication for an area-efficient FFT architecture. A standard multi-radix-24,22,23 FFT with a single-path delay feedback structure is considered. Vedic multipliers employ the Urdhva Tiryakbhyam method, which reduces redundant steps and generates parallel partial products. The proposed 4–2 compressor adders have been introduced inside the vedic multiplier to minimize carry delay and speed up the multiplication process. The vedic multiplier designed on the compressor adder saves power and gate count. The devised FFT algorithm is implemented using 45nm CMOS technology. Simulation results show a gate reduction of 21.5% and power consumption of 18.5%. The throughput had increased to 1.86 GS/s at 186 MHz compared to existing FFT architectures.

Feedback delay of sports intelligent learning system based on model predictive control and artificial intelligence

At present, in terms of model predictive control theory and model applications, two-layer segmented linear grid models are dominant. The two-layer piecewise linear lattice model is more effective, does not require too many parameters and is easy to calculate. Since the multi-layer model predictive control is based on a two-layer model, it is very important to study the mechanism and optimization methods of the two-layer model. Artificial intelligence comes from computer science. It tries to understand the nature of intelligence and create new intelligent machines that can react like human intelligence. Research in this field involves robotics, speech recognition, image recognition, natural language processing, etc. Since the emergence of artificial intelligence, theory and technology have gradually matured, and its application fields have also increased. The technological products created by artificial intelligence will embody the development of human wisdom in the future. Sports intelligence learning was first proposed by Lins. Linsley found that under laboratory conditions, by observing and recording the learner's behavior frequency and reaction speed, and adjusting the learning activities based on this, a better learning effect can be obtained. The combination of sports intelligence learning and behaviorist learning theory forms a systematic and accurate teaching method. Video system feedback delayed learning is a part of multimedia education technology. In recent years, multimedia technology has been widely used in various educational fields. By reviewing the application research of multimedia teaching technology in education, we have determined the areas related to the delay of the video system feedback, and guided the application research of the video feedback system in education.

Understanding Effects of Visual Feedback Delay in AR on Fine Motor Surgical Tasks.

Latency is a pervasive issue in various systems that can significantly impact motor performance and user perception. In medical settings, latency can hinder surgeons' ability to quickly correct movements, resulting in an experience that doesn't align with user expectations and standards of care. Despite numerous studies reporting on the negative effects of latency, there is still a gap in understanding how it impacts the use of augmented reality (AR) in medical settings. This study aims to address this gap by examining how latency impacts motor task performance and subjective perceptions, such as cognitive load, on two display types: a monitor display, traditionally used inside an operating room (OR), and a Microsoft HoloLens 2 display. Our findings indicate that both level of latency and display type impact motor performance, and higher latencies on the HoloLens result in relatively poor performance. However, cognitive load was found to be unrelated to display type or latency, but was dependent on the surgeon's training level. Surgeons did not compromise accuracy to gain more speed and were generally well aware of the latency in the system irrespective of their performance on task. Our study provides valuable insights into acceptable thresholds of latency for AR displays and proposes design implications for the successful implementation and use of AR in surgical settings.

Characterization of a Family of Controllers for Networked Systems Under Nonuniform Communication and Network-Induced Delay

In this note, we characterize a family of discrete-time strictly causal stabilizing controllers for networked systems under nonuniform communication and network-induced delays. First, we absorb the feedback delay in the controller structure and parameterize a family of stabilizing controllers for the delay-free plant with some restrictions on the controller structure due to time delay. Then we lift the feedback connection and choose the free parameter of the family in the lifted domain to incorporate the effect of nonuniform communication, resulting in a family of stabilizing controllers under nonuniform communication and delay. Further, we propose a network-friendly architecture that, contrary to existing results, does not require computing a control sequence at the sensor side of the controller and is robust against network packet dropouts. Furthermore, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_{2}$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_\infty$</tex-math></inline-formula> optimization are discussed. Finally, examples of a stabilizing controller and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}_\infty$</tex-math></inline-formula> controller illustrate the effectiveness of the proposed techniques.

The effect of delay feedback control on dynamics of a stochastic Internet congestion control model

The effect of delay feedback control on dynamics of a stochastic Internet congestion control model

Delay feedback control of highly nonlinear neutral stochastic delay differential equations driven by G-Brownian motion

Delay feedback control of highly nonlinear neutral stochastic delay differential equations driven by G-Brownian motion

New Criteria for Analyzing the Permanence, Periodic Solution, and Global Attractiveness of the Competition and Cooperation Model of Two Enterprises with Feedback Controls and Delays

This paper studies a class of the non-autonomous competition and cooperation model of two enterprises involving discrete time delays and feedback controls. The paper proposes new criteria for analyzing the permanence, periodic solution, and global attractiveness of the model. The common mathematical techniques of the Lyapunov method, the continuation theorem, and the comparison principle are used in this paper. By means of the comparison principle and inequality techniques, the concept of permanence is investigated, which refers to the long-term survival of the enterprises within the competitive and cooperative framework. Meanwhile, using the continuation theorem, we establish conditions under which the system exhibits periodic behavior. Additionally, the global attractiveness of the system is derived by constructing multiple Lyapunov functionals. Finally, an example is presented to illustrate the applicability and validity of the proposed criteria in this paper. This example serves as a demonstration that showcases the main results derived from the analysis.

Synchronization analysis of nabla fractional-order fuzzy neural networks with time delays via nonlinear feedback control

This paper is committed to explore synchronization issues for a class of nabla fractional-order fuzzy neural networks with time delays. First, we establish two useful nabla fractional inequalities by feat of the theory of nabla fractional calculus and N-transform together with nabla convolution. Next, we design two distinctive controllers including nonlinear delay feedback controller and hybrid nonlinear delay controller, some easily verified quasi-synchronization (QS) criteria and complete synchronization (CS) criteria are derived by virtue of newly proposed inequalities therein and some inequality techniques. Finally, the correctness of theoretical results is indicated finally through numerical simulations. What is more important, theoretical results therein can offer some new avenues about QS and CS analysis for nabla fractional dynamical networks.

Exponential stability result for the wave equation with Kelvin–Voigt damping and past history subject to Wentzell boundary condition and delay term

In this paper, we present an analysis of stability of solutions corresponding to a variable coefficient's wave equation subject to a locally Kelvin–Voigt damping and distributed effect driven by a nonnegative function with dynamic Wentzell boundary conditions and delay term. By using frequency domain approach method, we show that under a suitable assumption between the internal damping function and the boundary delay feedback, considering some geometrical assumptions on the boundary of , supposing that the relaxation function decay exponentially to zero, that the energies of the problem decay exponentially to zero.

Stability and bifurcation control of a delayed fractional eco-epidemiological system with saturated incidence

This paper proposes a delayed feedback control strategy for a fractional ecological infectious disease system with infected predators. Firstly, for the uncontrolled system, the stability of each equilibrium is discussed. Choosing the gestational delay as the branching parameter, the conditions of Hopf bifurcation are given at the positive equilibrium. The results show that the stable domain for the fractional system is larger than that for the integer-order system. Secondly, for the controlled system, the effects of gestational delay and feedback delay on the induction of the Hopf bifurcation are investigated, respectively. In addition, we find that the feedback gain coefficient also changes the critical value at which Hopf bifurcation occurs. Selecting a suitable feedback controller can effectively extend the stable domain of the system compared to the control-free system. Finally, the accuracy and effectiveness of the delay feedback controller in controlling the bifurcation are verified through numerical simulations.

Online Distributed Learning for Aggregative Games With Feedback Delays

This paper proposes a new aggregative game (AG) model with feedback delays. The strategies of players are selected from given strategy sets and subject to global nonlinear inequality constraints. Both cost functions and constrained functions of players are time-varying, which reflects the changing nature of environments. At each time, each player only has access to its strategy set information, and the information of its current cost function and current constrained function is unknown. Due to feedback delays, the feedback information of corresponding cost functions and constrained functions is not revealed to players immediately after the selection of strategies. It would take a period of time for players to observe their feedback information. To address such an AG problem, a distributed learning algorithm is proposed with the local information from their neighbors and the delayed feedback information from environments, and it is applicable to time-varying weighted digraphs. We find that the two metrics of the algorithm grow sub-linearly with respect to the learning time. A simulation example is given to illustrate the performance of the proposed algorithm.