Signal modeling and impulse response shaping for semiconductor detectors

The output-signal models and impulse response shaping(IRS)functions of semiconductor detectors are important for establishing high-precision measurement systems.In this paper,an output-signal model for semiconductor detector systems is proposed.According to the proposed model,a multistage cascade deconvolution IRS algorithm was developed using the C-R inverse system,R-C inverse system,and differentiator system.The silicon drift detector signals acquired from the analog-to-digital converter were tested.The experimental results indicated that the shaped pulses obtained using the proposed model had no undershoot,and the average peak base width of the output shaped pulses was reduced by 36%compared with that for a simple model proposed in a previous work[1].Offline processing results indicated that compared with the traditional IRS algorithm,the average peak base width of the output shaped pulses obtained using the proposed algorithm was reduced by 11%,and the total elapsed time required for pulse shaping was reduced by 26%.The proposed algorithm avoids recursive calculation.If the sampling frequency of the digital system reaches 100 MHz,the proposed algorithm can be simplified to integer arithmetic.The proposed IRS algorithm can be applied to high-resolution energy spectrum analysis,highcounting rate energy spectrum correction,and coincidence and anti-coincidence measurements.

Predictive functional control of integrating process based on impulse response

The predictive model is built according to the characteristics of the impulse response of integrating process. In order to eliminate the permanent offset between the setpoint and the process output in the presence of the load disturbance, a novel error compensation method is proposed. Then predictive functional control of integrating process is designed. The method given generates a simple control structure, which can significandy reduce online computation. Furthermore, the tuning of the controller is fairly straightforward. Simulation results indicate that the designed control system is relatively robust to the parameters variation of the process.

The time reversal effect of the impulse response of crust

In this paper, the time reversal processes of impulse response of crust are simulated by means of a dynamical finite element method (DFEM). The results indicate that a small undulating load during a long period may cause a focused brevity impact in a chaos-response system. The physical principle for this phenomenon is that the wave interferes or multiples superposition. Based on this knowledge, a new view toward the mechanism for preparing and triggering an earthquake is proposed. Finally, an interpretation of crust response to the sea tides is given.

Modeling personalized head-related impulse response using support vector regression

A new customization approach based on support vector regression （SVR） is proposed to obtain individual headrelated impulse response （HRIR） without complex measurement and special equipment. Principal component analysis （PCA） is first applied to obtain a few principal components and corresponding weight vectors correlated with individual anthropometric parameters. Then the weight vectors act as output of the nonlinear regression model. Some measured anthropometric parameters are selected as input of the model according to the correlation coefficients between the parameters and the weight vectors. After the regression model is learned from the training data, the individual HRIR can be predicted based on the measured anthropometric parameters. Compared with a back-propagation neural network （BPNN） for nonlinear regression, better generalization and prediction performance for small training samples can be obtained using the proposed PCA-SVR algorithm.

Interpreting Dose-Response Relation for Exposure to Multiple Sound Impulses in the Framework of Immunity

Hearing loss is a common military health problem and it is closely related to exposures to impulse noises from blast explosions and weapon firings. In a study based on test data of chinchillas and scaled to humans (Military Medicine, 181: 59-69), an empirical injury model was constructed for exposure to multiple sound impulses of equal intensity. Building upon the empirical injury model, we conduct a mathematical study of the hearing loss injury caused by multiple impulses of non-uniform intensities. We adopt the theoretical framework of viewing individual sound exposures as separate injury causing events, and in that framework, we examine synergy for causing injury (fatigue) or negative synergy (immunity) or independence among a sequence of doses. Starting with the empirical logistic dose-response relation and the empirical dose combination rule, we show that for causing injury, a sequence of sound exposure events are not independent of each other. The phenomenological effect of a preceding event on the subsequent event is always immunity. We extend the empirical dose combination rule, which is applicable only in the case of homogeneous impulses of equal intensity, to accommodate the general case of multiple heterogeneous sound exposures with non-uniform intensities. In addition to studying and extending the empirical dose combination rule, we also explore the dose combination rule for the hypothetical case of independent events, and compare it with the empirical one. We measure the effect of immunity quantitatively using the immunity factor defined as the percentage of decrease in injury probability attributed to the sound exposure in the preceding event. Our main findings on the immunity factor are: 1) the immunity factor is primarily a function of the difference in SELA (A- weighted sound exposure level) between the two sound exposure events;it is virtually independent of the magnitude of the two SELA values as long as the difference is fixed;2) the immunity factor increases monotonically from 0 to 100% as the first dose is varied from being significantly below the second dose, to being moderately above the second dose. The extended dose-response formulation developed in this study provides a theoretical framework for assessing the injury risk in realistic situations.

Continuous-Time and Discrete-Time Singular Value Decomposition of an Impulse Response Function

This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Four optimal design approaches of high-order finite-impulse response filters based on neural network

Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms to approximate the desired frequency response specification. Therefore, these methods avoid matrix inversion, and make a fast calculation of the filter’s coefficients possible. The convergence theorems of these proposed algorithms were presented and proved to illustrate them stable, and the implementation of these methods was described together with some design guidelines. The simulation results show that the ripples of the designed FIR filters are significantly little in the pass-band and stop-band, and the proposed algorithms are of fast convergence.

Interval analysis method and convex models for impulsive response of structures with uncertain-but-bounded external loads

Two non-probabilistic, set-theoretical methods for determining the maximum and minimum impulsive responses of structures to uncertain-but-bounded impulses are presented. They are, respectively, based on the theories of interval mathematics and convex models. The uncertain-but-bounded impulses are assumed to be a convex set, hyper-rectangle or ellipsoid. For the two non-probabilistic methods, less prior information is required about the uncertain nature of impulses than the probabilistic model. Comparisons between the interval analysis method and the convex model, which are developed as an anti-optimization problem of finding the least favorable impulsive response and the most favorable impulsive response, are made through mathematical analyses and numerical calculations. The results of this study indicate that under the condition of the interval vector being determined from an ellipsoid containing the uncertain impulses, the width of the impulsive responses predicted by the interval analysis method is larger than that by the convex model; under the condition of the ellipsoid being determined from an interval vector containing the uncertain impulses, the width of the interval impulsive responses obtained by the interval analysis method is smaller than that by the convex model.

Efficient computation for dynamic responses of systems with time-varying characteristics

Based on Neumman series and epsilon-algorithm, an efficient computation for dynamic responses of systems with arbitrary time-varying characteristics is investigated. Avoiding the calculation for the inverses of the equivalent stiffness matrices in each time step, the computation effort of the proposed method is reduced compared with the full analysis of Newmark method. The validity and applications of the proposed method are illustrated by a 4-DOF spring-mass system with periodical time-varying stiffness properties and a truss structure with arbitrary time-varying lumped mass. It shows that good approximate results can be obtained by the proposed method compared with the responses obtained by the full analysis of Newmark method.

Dynamics of a Nonautonomous Plant Disease Model with General Nonlinear Incidence Rate and Time-Varying Impulse

In this paper, for controlling the spread of plant diseases, a nonautonomous SEIS (Susceptible → Exposed → Infectious → Susceptible) epidemic model with a general nonlinear incidence rate and time-varying impulsive control strategy is proposed and investigated. This novel model could result in an objective criterion on how to control plant disease transmission by replanting of healthy plants and removal of infected plants. Using the method of small amplitude perturbation, the sufficient conditions under which guarantee the globally attractive of the disease-free periodic solution and the permanence of the disease are obtained, that is, the disease dies out if R12>1.

Impulsive control of nonlinear systems with time-varying delays

A whole impulsive control scheme of nonlinear systems with time-varying delays, which is an extension for impulsive control of nonlinear systems without time delay, is presented in this paper. Utilizing the Lyapunov functions and the impulsive-type comparison principles, we establish a series of different conditions under which impulsively controlled nonlinear systems with time-varying delays are asymptotically stable. Then we estimate upper bounds of impulse interval and time-varying delays for asymptotically stable control. Finally a numerical example is given to illustrate the effectiveness of the method.

An improved impulsive control approach to nonlinear systems with time-varying delays

A scheme for the impulsive control of nonlinear systems with time-varying delays is investigated in this paper. Based on the Lyapunov-like stability theorem for impulsive functional differential equations （FDEs）, some sufficient conditions are presented to guarantee the uniform asymptotic stability of impulsively controlled nonlinear systems with time-varying delays. These conditions are more effective and less conservative than those obtained. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

Identifi cation of model structure parameters via combination of AFMM and ARX from seismic response data

To identify the model structure parameters in shaking table tests from seismic response, especially from time- varying response records, this paper presents a new methodology by combining the online recursive Adaptive Forgetting through Multiple Models （AFMM） and offtine Auto-Regression with eXogenous variables （ARX） model. First, the AFMM is employed to detect whether the response of model structure is time-invariant or time-varying when subjected to strong motions. Second, if the response is time-invariant, the modal parameters are identified from the entire response record, such as the acceleration time-history using the ARX model. If the response is time-varying, the acceleration record is divided into three segments according to the accurate time-varying points detected by AFMM, and parameters are identified by only using the tail segment data, which is time-invariant and suited for analysis by the ARX model. Finally, the changes in dynamic properties due to various strong motions are obtained using the presented methodology. The feasibility and advantages of the method are demonstrated by identifying the modal parameters of a 12-story reinforced concrete （RC） frame structure in a shaking table test.

Global qualitative analysis of new Monod type chemostat model with delayed growth response and pulsed input in polluted environment

In this paper, we consider a new Monod type chemostat model with time delay and impulsive input concentration of the nutrient in a polluted environment. Using the discrete dynamical system determined by the stroboscopic map, we obtain a ＂microorganism-extinction＂ periodic solution. Further, we establish the sufficient conditions for the global attractivity of the microorganism-extinction periodic solution. Using new computational techniques for impulsive and delayed differential equation, we prove that the system is permanent under appropriate conditions. Our results show that time delay is ＂profitless＂.

Design of complex FIR filters with arbitrary magnitude and group delay responses

To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is based on a batch back-propagation neural network algorithm by directly minimizing the real magnitude error and phase error from the linear-phase to obtain the filter＇s coefficients. The approach can deal with both the real and complex coefficient FIR digital filters design problems. The main advantage of the proposed design method is the significant reduction in the group delay error. The effectiveness of the proposed method is illustrated with two optimal design examples.

WRIST FORCE SENSOR'S DYNAMIC PERFORMANCE CALIBRATION BASED ON NEGATIVE STEP RESPONSE

Negative step response experimental method is used in wrist force sensor＇s dynamic performance calibration. The exciting manner of negative step response method is the same as wrist force sensor＇s load in working. This experimental method needn＇t special experiment equipments. Experiment＇s dynamic repeatability is good. So wrist force sensor＇s dynamic performance is suitable to be calibrated by negative step response method. A new correlation wavelet transfer method is studied. By wavelet transfer method, the signal is decomposed into two dimensional spaces of time-frequency. So the problem of negative step exciting energy concentrating in the low frequency band is solved. Correlation wavelet transfer doesn＇t require that wavelet primary function be orthogonal and needn＇t wavelet reconstruction. So analyzing efficiency is high. An experimental bench is designed and manufactured to load the wrist force sensor orthogonal excitation force/moment. A piezoelectric force sensor is used to setup soft trigger and calculate the value of negative step excitation. A wrist force sensor is calibrated. The pulse response function is calculated after negative step excitation and step response have been transformed to positive step excitation and step response. The pulse response function is transferred to frequency response function. The wrist force sensor＇s dynamic characteristics are identified by the frequency response function.

Recommendation application for video head impulse test based on fuzzy logic control

Vestibulo-ocular reflex(VOR) is an important biological reflex that controls eye movement to ensure clear vision while the head is in motion.Nowadays,VOR measurement is commonly done with a video head impulse test based on a velocity gain algorithm or a position gain algorithm,in which velocity gain is a VOR calculation on head and eye velocity,whereas position gain is calculated from head and eye position.The aim of this work is first to compare the two algorithms' performance and to detect covert catch-up saccade,then to propose a stand-alone recommendation application for the patient's diagnosis.In the first experiment,for ipsilesional and contralesional sides,the calculated position gain(0.94±0.17) is higher than velocity gain(0.84±0.19).Moreover,gain asymmetry of both lesion and intact sides using velocity gain is mostly higher than that from using position gain(four out of five subjects).Consequently,for subjects who have unilateral vestibular neuritis diagnosed from clinical symptoms and a vestibular function test,vestibular weakness is depicted by velocity gain much better than by position gain.Covert catch-up saccade and position gain then are used as inputs for recommendation applications.

Risk of Hearing Loss Caused by Multiple Acoustic Impulses in the Framework of Biovariability

We consider the hearing loss injury among subjects in a crowd with a wide spectrum of individual intrinsic injury probabilities due to biovariability. For multiple acoustic impulses, the observed injury risk of a crowd vs the effective combined dose follows the logistic dose-response relation. The injury risk of a crowd is the average fraction of injured. The injury risk was measured in experiments as follows: each subject is individually exposed to a sequence of acoustic impulses of a given intensity and the injury is recorded;results of multiple individual subjects were assembled into data sets to mimic the response of a crowd. The effective combined dose was adjusted by varying the number of impulses in the sequence. The most prominent feature observed in experiments is that the injury risk of the crowd caused by multiple impulses is significantly less than the value predicted based on assumption that all impulses act independently in causing injury and all subjects in the crowd are statistically identical. Previously, in the case where all subjects are statistically identical (i.e., no biovariability), we interpreted the observed injury risk caused by multiple impulses in terms of the immunity effects of preceding impulses on subsequent impulses. In this study, we focus on the case where all sound exposure events act independently in causing injury regardless of whether one is preceded by another (i.e., no immunity effect). Instead, we explore the possibility of interpreting the observed logistic dose-response relation in the framework of biovariability of the crowd. Here biovariability means that subjects in the crowd have their own individual injury probabilities. That is, some subjects are biologically less or more susceptible to hearing loss injury than others. We derive analytically the distribution of individual injury probability that produces the observed logistic dose-response relation. For several parameter values, we prove that the derived distribution is mathematically a proper density function. We further study the asymptotic approximations for the density function and discuss their significance in practical numerical computation with finite precision arithmetic. Our mathematical analysis implies that the observed logistic dose-response relation can be theoretically explained in the framework of biovariability in the absence of immunity effect.

Dynamic Response and Oscillating Behaviour of Fractionally Damped Beam

This paper presents the numerical solution of a viscoelastic continuous beam whose damping behaviours are defined in term of fractional derivatives of arbitrary order.Homotopy Perturbation Method(HPM)is used to obtain the dynamic response with respect to unit impulse load.Obtained results are depicted in term of plots.Comparisons are made with the analytic solutions obtained by Zu-feng and Xiao-yan(2007)to show the effectiveness and validation of the present method.