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.

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.

High Order Stable Infinite Impulse Response Filter Design Using Cuckoo Search Algorithm

In this paper, an efficient technique for optimal design of digital infinite impulse response （IIR） filter with minimum passband error （ep）, minimum stopband error （es）, high stopband attenuation （As）, and also free from limit cycle effect is proposed using cuckoo search （CS） algorithm. In the proposed method, error function, which is multi-model and non-differentiable in the heuristic surface, is constructed as the mean squared difference between the designed and desired response in frequency domain, and is optimized using CS algorithm. Computational efficiency of the proposed technique for exploration in search space is examined, and during exploration, stability of filter is maintained by considering lattice representation of the denominator polynomials, which requires less computational complexity as well as it improves the exploration ability in search space for designing higher filter taps. A comparative study of the proposed method with other algorithms is made, and the obtained results show that 90% reduction in errors is achieved using the proposed method. However, computational complexity in term of CPU time is increased as compared to other existing algorithms.

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service(DoS) attack,named the ‘primary user emulation attack(PUEA)', exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response(CIR) between the secondary user(SU) and the signal source is used to determine whether the received signal is transmitted by the primary user(PU) or the primary user emulator(PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.

An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification

In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefcient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.

High-Speed Fault-Tolerant Finite Impulse Response Digital Filter on Field Programmable Gate Array

Some fast finite impulse response (FIR) filters use a large number of look-up tables (LUTs) to configure distributed random-access memories (RAMs) and save registers. The distributed RAMs store 2M precomputed sums of M permuted operands in order to simplify the accumulation, which lays similarity to the solution of Boolean satisfiability (SAT) problem. In this work, a high-speed fault-tolerant FIR digital filter on field programmable gate array (FPGA) is proposed for hardware implementation. A shift register and an RAM are used to arrange the data flow. Generally, an N-tap digital filter only requires N embedded multipliers on FPGA. The better performance is due to high-radix words and low-latency operations. A 32-tap 8-bit FIR digital filter enjoys a throughput of 9.17 MB/s, taking 109 ns to calculate one convolution. In addition, a fault-tolerant scheme by majority logic is used to correct real-time errors within digital filters.

Optimal Linear Phase Finite Impulse Response Band Pass Filter Design Using Craziness Based Particle Swarm Optimization Algorithm

An efficient method is proposed for the design of finite impulse response(FIR) filter with arbitrary pass band edge,stop band edge frequencies and transition width.The proposed FIR band stop filter is designed using craziness based particle swarm optimization(CRPSO) approach.Given the filter specifications to be realized,the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics.In this paper,for the given problem,the realizations of the optimal FIR band pass filters of different orders have been performed.The simulation results have been compared with those obtained by the well accepted evolutionary algorithms,such as Parks and McClellan algorithm(PMA),genetic algorithm(GA) and classical particle swarm optimization(PSO).Several numerical design examples justify that the proposed optimal filter design approach using CRPSO outperforms PMA and PSO,not only in the accuracy of the designed filter but also in the convergence speed and solution quality.

A fast implementation for computing spatial impulse response of ultrasonic transducers

The spatial impulse response（SIR） method is often used as the ＇gold standard5 in simulation of transient acoustic wave fields due to its high accuracy in the linear domain.However, a high sampling frequency is often required in order to achieve the high accuracy. As a result, a large amount of data has to be processed. In this paper a fast approach for computing spatial impulse response is proposed to reduce the computation burden. The proposed approach is developed by employing the relationship of SIRs at observed points and SIRs of the projection points on the transducer surface. Two critical parameters used in the proposed approach, the calculation sampling frequency and the interpolation sampling frequency, are then analyzed.Results show that for a 2.25 MHz rectangular transducer with the size of 5 mm×10 mm,a calculation sampling frequency of 1000 MHz and an interpolation sampling frequency of500 MHz can achieve superior performance while improving the computation efficiency 18 times than the direct solving.

Research on the Relationship Between Environmental and Economic Coupling Systems in Bohai Bay Area Based on a Vector Autoregression(VAR)Model

This study analyzed the impact of land-based contaminants and tertiary industrial structure on economic development in the selected Bohai Bay area,China.Based on panel data spanning 2011-2020,a vector autoregressive(VAR)model is used to analyze and forecast the short-run and long-run relationships between three industrial structures,pollutant discharge,and economic development.The results showed that the environmental index had a long-term cointegration relationship with the industrial structure economic index.Per capital chemical oxygen demand(PCOD)and per capita ammonia nitrogen(PNH_(3)N)had a positive impact on delta per capita GDP(dPGDP),while per capita solid waste(PSW),the secondary industry rate(SIR)and delta tertiary industry(dTIR)had a negative impact on dPGDP.The VAR model under this coupling system had stability and credibility.The impulse response results showed that the short-term effect of the coupling system on dPGDP was basically consistent with the Granger causality test results.In addition,variance decomposition was used in this study to predict the long-term impact of the coupling system in the next ten periods(i.e.,ten years).It was found that dTIR had a great impact on dPGDP,with a contribution rate as high as 74.35%in the tenth period,followed by the contribution rate of PCOD up to 3.94%,while the long-term contribution rates of PSW,SIR and PNH3N were all less than 1%.The results show that the government should support the development of the tertiary industry to maintain the vitality of economic development and prevent environmental deterioration.

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.

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.

浅水声学通信中的多路径几何信道模型

Using the underwater acoustic channel(UWA)for information dissemination requires a high data rate.However,some phenomena like refraction,reflection,phase shift,and high attenuation are undesirably apparent when the subject of using UWA is raised.Accordingly,sound communication would be a highly challenging task to be accomplished.Therefore,proposing a model of acoustic underwater communication channels is critical because of the multipath interference originating from the surface and bottom of the ocean.In this contribution,a straightforward geometry channel model for vertical and horizontal marine communications is presented.To do so,transmission loss and channel impulse response are analyzed as a function of transmitter and receiver distance,water depth,and reflection rate.The results of the model proposed in this paper are in very good agreement with those available in the literature.Initial findings indicate that the delay spread of horizontal communication with a 1000 m range reaches79 ms and 0.3 s for 30 m vertical communication.

Are life insurance futures a safe haven during COVID‑19?

This study aims to examine whether life insurance futures can serve as a hedge against the COVID-19 pandemic and whether they have the characteristics of a safe haven under the impact of the health shocks of the COVID-19 pandemic.We chose three life insurance stock futures in India and one in Taiwan as samples,including the market index of the two countries and the number of confirmed COVID-19 cases as sample variables.We used the growth rate of COVID-19 cases as the threshold variable,esti-mated the asymmetric threshold vector autoregression model,and found that insur-ance futures in the regime with a significant growth rate of confirmed COVID-19 cases can hedge against COVID-19 risks;therefore,insurance futures are a safe haven for the market.We further estimated the time-varying parameter vector autoregression model,and the impulse response results showed that insurance futures are a safe haven for COVID-19 pandemic risks.

Characteristic of Line-of-Sight in Infrastructure-to-Vehicle Visible Light Communication Using MIMO Technique

Visible Light Communication(VLC)technology is aggressive research for the next generation of communication.Currently,Radio Frequency(RF)communication has crowed spectrum.An Intelligent Transportation System(ITS)has been improved in the communication network for Vehicle-to-Vehicle(V2 V),Vehicle-to-Infrastructure(V2I),and Infrastructure-to-Vehicle(I2V)by using the visible light spectrum instead of the RF spectrum.This article studies the characterization of Line-of-Sight(LOS)optical performance in an Outdoor Wireless Visible Light Communication(OWVLC)system employing a Multiple-Input Multiple-Output(MIMO)technique for I2V communications in ITS regulations.We design the new configuration of the OWVLC-I2V system,which is an alternative approach to communication for I2V system at nighttime.The results show the Channel Impulse Response(CIR)of the LOS links in visible light communication for I2V system in ITS by investigating the receiver on the vehicle moving along the coverage communication area.Furthermore,the OWVLC-I2V system using the MIMO technique depicts the performance of throughput and Bit Error Rate(BER)vs.vehicle speed while the vehicle passes a street light.

Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review

In this paper,we highlight some recent developments of a new route to evaluate macroeconomic policy effects,which are investigated under the framework with potential outcomes.First,this paper begins with a brief introduction of the basic model setup in modern econometric analysis of program evaluation.Secondly,primary attention goes to the focus on causal effect estimation of macroeconomic policy with single time series data together with some extensions to multiple time series data.Furthermore,we examine the connection of this new approach to traditional macroeconomic models for policy analysis and evaluation.Finally,we conclude by addressing some possible future research directions in statistics and econometrics.

FPGA-Based Efficient Programmable Polyphase FIR Filter

The modelling, design and implementation of a high-speed programmable polyphase finite impulse response (FIR) filter with field programmable gate array (FPGA) technology are described. This FIR filter can run automatically according to the programmable configuration word including symmetry/asymmetry, odd/even taps, from 32 taps up to 256 taps. The filter with 12 bit signal and 12 bit coefficient word-length has been realized on a Xilinx VirtexⅡ-v1500 device and operates at the maximum sampling frequency of (160 MHz.)