In this paper, we study the problem of high stability code tracking for band-limited direct sequence spread spectrum (DSSS) systems. In band-limited DSSS systems carrying critical applications, high stability is required in addition to low error variance for code tracking. Therefore, we propose a high stability code tracking method for band-limited DSSS systems, which constructs frequency domain vectors from the received signal, reduces the dimension of the vectors by frequency domain integration and dump, and estimates the time-delay error by the subspace method. We also give a closed-form expression for the steady-state time-delay error variance of the proposed method, which can be used to analyze the error variance performance theoretically and design proper band-limited DSSS systems. The theoretical analysis and simulation results show that the proposed method is able to enhance both the maximum and linear code tracking ranges, thus realizing high stability code tracking, and has constant error variance performance and appropriate computational complexity.

A state-space approach for adaptive second-order IIR notch digital filters is explored. A simplified iterative algorithm is derived from the gradient-descent method to minimize the mean-squared output of an adaptive notch digital filter. The stability and parameter-estimation bias are then analyzed by employing a first-order linear dynamical system. As a consequence, it is clarified that the resulting parameter estimate is unbiased. Finally, a numerical example is presented to demonstrate the validity and effectiveness of the adaptive state-space notch digital filter and bias analysis of parameter estimation.

The steady-state and convergence performances are important indicators to evaluate adaptive algorithms. The step-size affects these two important indicators directly. Many relevant scholars have also proposed some variable step-size adaptive algorithms for improving performance. However, there are still some problems in these existing variable step-size adaptive algorithms, such as the insufficient theoretical analysis, the imbalanced performance and the unachievable parameter. These problems influence the actual performance of some algorithms greatly. Therefore, we intend to further explore an inherent relationship between the key performance and the step-size in this paper. The variation of mean square deviation (MSD) is adopted as the cost function. Based on some theoretical analyses and derivations, a novel variable step-size algorithm with a dynamic limited function (DLF) was proposed. At the same time, the sufficient theoretical analysis is conducted on the weight deviation and the convergence stability. The proposed algorithm is also tested with some typical algorithms in many different environments. Both the theoretical analysis and the experimental result all have verified that the proposed algorithm equips a superior performance.

When a mathematical model is not available for a dynamical system, it is reasonable to use a data-driven approach for analysis and control of the system. With this motivation, the authors have recently developed a data-driven solution to Lyapunov equations, which uses not the model but the data of several state trajectories of the system. However, the number of state trajectories to uniquely determine the solution is O(n2) for the dimension n of the system. This prevents us from applying the method to a case with a large n. Thus, this paper proposes a novel class of data-driven Lyapunov equations, which requires a smaller amount of data. Although the previous method constructs one scalar equation from one state trajectory, the proposed method constructs three scalar equations from any combination of two state trajectories. Based on this idea, we derive data-driven Lyapunov equations such that the number of state trajectories to uniquely determine the solution is O(n).

We investigated the photochemical stability of an electro-optic (EO) polymer under laser irradiation at 1310nm to reveal photodegradation mechanisms. It was found that one-photon absorption excitation assisted with the thermal energy at the temperature is involved in the photodegradation process, in contrast to our previous studies at a wavelength of 1550nm where two-photon absorption excitation is involved in the photodegradation process. Thus, both the excitation wavelength and the thermal energy strongly affect to the degradation mechanism. In any cases, the photodegradation of EO polymers is mainly related to the generation of exited singlet oxygen.

This paper deals with a state-space approach for adaptive second-order IIR notch digital filters with constrained poles and zeros. A simplified iterative algorithm is derived from the gradient-descent method to minimize the mean-squared output of an adaptive notch digital filter. Then, stability and parameter-estimation bias are analyzed for the simplified iterative algorithm. A numerical example is presented to demonstrate the validity and effectiveness of the proposed adaptive state-space notch digital filter and parameter-estimation bias analysis.

We present a mathematical formulation of a trust metric using a quality and quantity pair. Under a certain assumption, we regard trust as an additive value and define the soundness of a trust computation as not to exceed the total sum. Moreover, we point out the importance of not only soundness of each computed trust but also the stability of the trust computation procedure against changes in trust value assignment. In this setting, we define trust composition operators. We also propose a trust computation protocol and prove its soundness and stability using the operators.

This letter studies a biobjective optimization problem in binary associative memories characterized by ternary connection parameters. First, we introduce a condition of parameters that guarantees storage of any desired memories and suppression of oscillatory behavior. Second, we define a biobjective problem based on two objectives that evaluate uniform stability of desired memories and sparsity of connection parameters. Performing precise numerical analysis for typical examples, we have clarified existence of a trade-off between the two objectives.

Feature selection based on particle swarm optimization is often employed for promoting the performance of artificial intelligence algorithms. However, its interpretability has been lacking of concrete research. Improving the stability of the feature selection method is a way to effectively improve its interpretability. A novel feature selection approach named Interpretable Particle Swarm Optimization is developed in this paper. It uses four data perturbation ways and three filter feature selection methods to obtain stable feature subsets, and adopts Fuch map to convert them to initial particles. Besides, it employs similarity mutation strategy, which applies Tanimoto distance to choose the nearest 1/3 individuals to the previous particles to implement mutation. Eleven representative algorithms and four typical datasets are taken to make a comprehensive comparison with our proposed approach. Accuracy, F1, precision and recall rate indicators are used as classification measures, and extension of Kuncheva indicator is employed as the stability measure. Experiments show that our method has a better interpretability than the compared evolutionary algorithms. Furthermore, the results of classification measures demonstrate that the proposed approach has an excellent comprehensive classification performance.

This paper proposes a switched pinning control method with a multi-rating mechanism for vehicle platoons. The platoons are expressed as multi-agent systems consisting of mass-damper systems in which pinning agents receive target velocities from external devices (ex. intelligent traffic signals). We construct model predictive control (MPC) algorithm that switches pinning agents via mixed-integer quadratic programmings (MIQP) problems. The optimization rate is determined according to the convergence rate to the target velocities and the inter-vehicular distances. This multi-rating mechanism can reduce the computational load caused by iterative calculation. Numerical results demonstrate that our method has a reduction effect on the string instability by selecting the pinning agents to minimize errors of the inter-vehicular distances to the target distances.

This paper investigates an adaptive notch digital filter that employs normal state-space realization of a single-frequency second-order IIR notch digital filter. An adaptive algorithm is developed to minimize the mean-squared output error of the filter iteratively. This algorithm is based on a simplified form of the gradient-decent method. Stability and frequency estimation bias are analyzed for the adaptive iterative algorithm. Finally, a numerical example is presented to demonstrate the validity and effectiveness of the proposed adaptive notch digital filter and the frequency-estimation bias analyzed for the adaptive iterative algorithm.

This paper studies a novel approach to analysis of switched dynamical systems in perspective of bifurcation and multiobjective optimization. As a first step, we analyze a simple switched dynamical system based on a boost converter with photovoltaic input. First, in a bifurcation phenomenon perspective, we consider period doubling bifurcation sets in the parameter space. Second, in a multiobjective optimization perspective, we consider a trade-off between maximum input power and stability. The trade-off is represented by a Pareto front in the objective space. Performing numerical experiments, relationship between the bifurcation sets and the Pareto front is investigated.

In this paper, we propose a novel single-template strategy based on a mean template set and locally/globally weighted dynamic time warping (LG-DTW) to improve the performance of online signature verification. Specifically, in the enrollment phase, we implement a time series averaging method, Euclidean barycenter-based DTW barycenter averaging, to obtain a mean template set considering intra-user variability among reference samples. Then, we acquire a local weighting estimate considering a local stability sequence that is obtained analyzing multiple matching points of an optimal match between the mean template and reference sets. Thereafter, we derive a global weighting estimate based on the variable importance estimated by gradient boosting. Finally, in the verification phase, we apply both local and global weighting methods to acquire a discriminative LG-DTW distance between the mean template set and a query sample. Experimental results obtained on the public SVC2004 Task2 and MCYT-100 signature datasets confirm the effectiveness of the proposed method for online signature verification.

This paper proposes a technique that increases the lifetime of large scale integration (LSI) devices. As semiconductor technology improves at miniaturizing transistors, aging effects due to bias temperature instability (BTI) seriously affects their lifetime. BTI increases the threshold voltage of transistors thereby also increasing the delay of an electronics device, resulting in failures due to timing violations. To compensate for aging-induced timing violations, we exploit configurable approximate computing. Assuming that target circuits have exact and approximate modes, they are configured for the approximate mode if an aging sensor predicts violations. Experiments using an example circuit revealed an increase in its lifetime to >10 years.

The electric properties of a field-effect transistor not only depend on gate surface sidewall but also on channel orientation when applying channel stain engineering. The change of the gate surface and channel orientation through the rotated FinFETs provides the capability to compare the orientation dependence of performance and reliability. This study characterized the <100> and <110> channels of FinFETs on the same wafer under tensile and compressive stresses by cutting the wafer into rectangular silicon pieces and evaluated their piezoresistance coefficients. The piezoresistance coefficients of the <100> and <110> silicon under tensile and compressive stresses were first evaluated based on the current setup. Tensile stresses enhance the mobilities of both <100> and <110> channels, whereas compressive stresses degrade them. Electrical characterization revealed that the threshold voltage variation and drive current degradation of the {100} surface were significantly higher than those of {110} for positive bias temperature instability and hot carrier injection with equal gate and drain voltage (VG=VD). By contrast, insignificant difference is noted for the subthreshold slope degradation. These findings imply that a higher ratio of bulk defect trapping is generated by gate voltage on the <100> surface than that on the <110> surface.

This paper studies synchronization phenomena in a ring-coupled system of digital spiking neurons. The neuron consists of two shift registers connected by a wiring circuit and can generate various spike-trains. Applying a spike based connection, the ring-coupled system is constructed. The ring-coupled system can generate multi-phase synchronization phenomena of various periodic spike-trains. Using a simple dynamic model, existence and stability of the synchronization phenomena are analyzed. Presenting a FPGA based test circuit, typical synchronization phenomena are confirmed experimentally.

We propose a method to derive the loop gain from the open-loop and closed-loop output impedances in a dc-dc buck converter with voltage mode and current mode controls. This enables the loop gain to be measured without injecting a signal into the feedback loop, i.e. without breaking the feedback loop; hence the proposed method can be applied to the control circuits implemented on an IC. Our simulation and experiment show that the loop gain determined by the proposed method closely matches that yielded by the conventional method, which has to break the feedback loop. These results confirm that the proposed method can accurately estimate the phase margin.

A design-for-testability method and an electrical interconnect test method are proposed to detect open defects occurring at interconnects among dies and input/output pins in 3D stacked ICs. As part of the design method, an nMOS and a diode are added to each input interconnect. The test method is based on measuring the quiescent current that is made to flow through an interconnect to be tested. The testability is examined both by SPICE simulation and by experimentation. The test method enabled the detection of open defects occurring at the newly designed interconnects of dies at experiments test speed of 1MHz. The simulation results reveal that an open defect generating additional delay of 279psec is detectable by the test method at a test speed of 200MHz beside of open defects that generate no logical errors.

In this research, we propose an effective stability analysis method to impacting systems with periodically moving borders (periodic borders). First, we describe an n-dimensional impacting system with periodic borders. Subsequently, we present an algorithm based on a stability analysis method using the monodromy matrix for calculating stability of the waveform. This approach requires the state-transition matrix be related to the impact phenomenon, which is known as the saltation matrix. In an earlier study, the expression for the saltation matrix was derived assuming a static border (fixed border). In this research, we derive an expression for the saltation matrix for a periodic border. We confirm the performance of the proposed method, which is also applicable to systems with fixed borders, by applying it to an impacting system with a periodic border. Using this approach, we analyze the bifurcation of an impacting system with a periodic border by computing the evolution of the stable and unstable periodic waveform. We demonstrate a discontinuous change of the periodic points, which occurs when a periodic point collides with a border, in the one-parameter bifurcation diagram.

In this paper, operator-based reset control for a class of nonlinear systems with unknown bounded disturbance is considered using right coprime factorization approach. In detail, firstly, for dealing with the unknown bounded disturbance of the nonlinear systems, operator-based reset control framework is proposed based on right coprime factorization. By the proposed framework, robust stability of the nonlinear systems with unknown bounded disturbance is guaranteed by using the proposed reset controller. Secondly, under the reset control framework, an optimal design scheme is discussed for minimizing the error norm based on the proposed operator-based reset controller. Finally, for conforming effectiveness of the proposed design scheme, a simulation example is given.