Sequential tests for integrated-circuit failures

We propose a sequential probability ratio test (SPRT) based on a 2-parameter Weibull distribution for integrated-circuit (IC) failure analysis. The shape parameter of the Weibull distribution characterizes the decreasing, constant, or increasing failure rate regions in the bath tub model for IC. The algorithm (SD) detects the operating region of the IC based on the observed failure times. Unlike the fixed-length tests, the SD, due to its sequential nature, uses the minimum average number of devices for the test for fixed error tolerances in the detection procedure. We find that SD is, on average, 96% more statistically efficient than the fixed-length test. SD is highly robust to the variations in the model parameters, unlike other existing sequential tests. Since the accuracy of the tests and the test length are conflicting requirements, we also propose a truncated SD which allows a better control of this tradeoff. It has both the sequential nature of examining measurements and the fixed-length property of guaranteeing that the tolerances be met approximately with a specified number of available measurements     

Capacity of a synchronous BFSK frequency-hopped multiple accesssystem with RTT erasure decision

The capacity of binary frequency shift keying (BFSK) frequency-hopped multiple access (FHMA) systems with side information is derived. The use of erasure decision with ratio-threshold test (RTT) for generating side information in fading and non-fading channels is investigated. The authors demonstrate the benefits of using erasure decision, achievable maximum capacity, optimum threshold setting and the optimal number of users in order to maximise the capacity     

Electrical impedance tomography of translationally uniform cylindrical objects with general cross-sectional boundaries

An algorithm is developed for electrical impedance tomography (EIT) of finite cylinders with general cross-sectional boundaries and translationally uniform conductivity distributions. The electrodes for data collection are assumed to be placed around a cross-sectional plane; therefore, the axial variation of the boundary conditions and the potential field are expanded in Fourier series. For each Fourier component a two-dimensional (2-D) partial differential equation is derived. Thus the 3-D forward problem is solved as a succession of 2-D problems, and it is shown that the Fourier series can be truncated to provide substantial savings in computation time. The finite element method is adopted and the accuracy of the boundary potential differences (gradients) thus calculated is assessed by comparison to results obtained using cylindrical harmonic expansions for circular cylinders. A 1016-element and 541-node mesh is found to be optimal. The algorithm is applied to data collected from phantoms, and the errors incurred from the several assumptions of the method are investigated.     

A closed-form performance upper-bound on the finite-length MMSE-DFEwith arbitrary decision delay

A simple analytical upper-bound on the decision-point SNR of the unbiased finite-length MMSE-DFE with arbitrary decision delay is derived. The bound can be easily computed given the channel impulse response, input SNR, length of feedforward filter, and desired decision delay. The bound is shown to be tighter than the matched-filter bound. A by-product is a computationally-efficient method for setting the decision delay     

A Linear Prediction Based Estimation of Signal‐to‐Noise Ratio in AWGN Channel

Most signal‐to‐noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)‐free symbols. In severe channel distortion where ISI is significant, the performance of these estimators badly deteriorates. We propose an SNR estimator which can operate on data samples collected at the front‐end of a receiver or at the input to the decision device. This will relax the restrictions over channel distortions and help extend the application of SNR estimators beyond system monitoring. The proposed estimator uses the characteristics of the second order moments of the additive white Gaussian noise digital communication channel and a linear predictor based on the modified‐covariance algorithm in estimating the SNR value. The performance of the proposed technique is investigated and compared with other in‐service SNR estimators in digital communication channels. The simulated performance is also compared to the Cramér‐Rao bound as derived at the input of the decision circuit.     

Adaptive sequential detection of target trajectory using decision statistics of pips at the unknown signal-to-noise ratio

Adaptive algorithms of multialternative sequential detection of target trajectory using the upper and lower thresholds and employing decision statistics of pips at the unknown signal-to-noise ratio (SNR) have been derived on the basis of the sequential criterion of simple complement. The application of lower thresholds made it possible to implement the procedure of discarding unsuccessful hypotheses. An adaptive two-alternative sequential algorithm of target track detection was developed using decision statistics of pips with SNR estimation by the criterion of error mean square minimum. The statistical simulation was used to analyze the algorithms for the case of target track detection on the basis of data of the surveillance radar that measures the range and radial velocity of target.     

Coding for Frequency-Hopped Spread-Spectrum Communication with Partial-Band Interference--Part I: Capacity and Cutoff Rate

The performance of optimal codes on frequency-hopped channels with partial-band interference is investigated. The performance measures considered are channel capacity and cutoff rate. Worst-case partial-band Gaussian noise interference is assumed with the interference independent of the transmitted signal. The capacity and cutoff rate are calculated as a function of the signal-to-noise ratio. We consider soft decision receivers and hard decision receivers with and without side information. Optimal code rates are found for each of the above cases. The required signal-to-noise ratio for reliable communication when codes are used is determined as a function of the code rate.     

Optimal Selection of Sequential Tests for Reliability

Reliability test requirements exist whereby truncated sequential test methods offer management the opportunity to minimize the s-expected cost of a test by optimal selection of the blend of resources that will be consumed by the test. The models presented here are useful in the real world design of reliability tests because of the ease of arriving at cost estimates and the existing availability of statistical distributional information on truncated sequential tests. The test parameters of sample size, number of spares, and duration of the test are amenable to optimization for reduction in the cost of reliability acceptance testing. When the various costs associated with the test are known, and the pdf and Sf of failures and/or time to test termination are defined, then minimum s-expected test costs are achievable. Constraints and sensitivity analysis can be applied to the models to assist the managerial decision process.     

On the Capacity and Energy Efficiency of Training-Based Transmissions Over Fading Channels

In this paper, the capacity and energy efficiency of training-based communication schemes employed for transmission over a priori unknown Rayleigh block-fading channels are studied. Initially, the case in which the product of the estimate error and transmitted signal is assumed to be Gaussian noise is considered. In this case, it is shown that bit energy requirements grow without bound as the signal-to-noise ratio (SNR) goes to zero, and the minimum bit energy is achieved at a nonzero SNR value below which one should not operate. The effect of the block length on both the minimum bit energy and the SNR value at which the minimum is achieved is investigated. Flash training and transmission schemes are analyzed and shown to improve the energy efficiency in the low-SNR regime. In the second part of this paper, the capacity and energy efficiency of training-based schemes are investigated when the channel input vector in each coherence block is subject to peak power constraints. The capacity-achieving input structure is characterized and the magnitude distribution of the optimal input is shown to be discrete with a finite number of mass points. The capacity, bit energy requirements, and optimal resource allocation strategies are obtained through numerical analysis. The improvements in energy efficiency when on-off keying (OOK) with fixed peak power and vanishing duty cycle is employed are studied.     

On optimal soft-decision demodulation

Wozencraft and Kennedy have suggested that the appropriate demodulator criterion of goodness is the cutoff rate of the discrete memoryless channel (DMC) created by the modulation system; the criterion of goodness adopted in this paper is the "symmetric" cutoff rate which differs from the former criterion only in that the signals are assumed equally likely. Massey's necessary condition for optimal coherent demodulation of binary signals is generalized toM-ary signals. It is shown that the optimal demodulator decision regions in likelihood space are bounded by hyperplanes. An iterative method is formulated for finding these optimal decision regions from an initial "good guess." For additive white Gaussian noise (AWGN), the corresponding optimal decision regions in signal space are bounded by hypersurfaces with hyperplane asymptotes; these asymptotes themselves bound the decision regions of a demodulator which, in several examples, is shown to be virtually optimal. In many cases, the necessary condition for demodulator optimality is also sufficient, but a counterexample to its general sufficiency is given.     

Performance study of a maximum-likelihood receiver for FFH/BFSKsystems with multitone jamming

We derive the optimum structure of a maximum-likelihood (ML) receiver for a fast frequency-hopped binary frequency-shift-keying (FFH/BFSK) spread-spectrum (SS) communication system operating in the presence of multitone jamming (MTJ) and additive white Gaussian noise (AWGN). It is shown that the side information of noise variance, signal tone amplitude, and multiple interfering tone amplitude at each hop, as well as the computation of nonlinear modified Bessel function are required to implement the optimum ML receiver. We have also derived and analyzed two suboptimum receivers-namely, the ML-I and ML-II receivers-for large and small signal-to-noise ratio (SNR), respectively. Performance comparisons among various receivers show that the ML receiver gives the best performance, while the ML-I and ML-II receivers also outperform the other existing methods under both high and low SNR conditions     

Optimal mean velocity estimation for Doppler weather radars

Optimal Doppler velocity estimation is explored for a standard Gaussian signal measurement model and thematic maximum-likelihood (ML) and Bayes estimation. Because the model considered depends on a vector parameter [velocity, spectrum width (SW), and signal-to-noise ratio (SNR)], the exact formulation of an ML or Bayes solution involves a system of coupled equations that cannot be made explicit for any of the parameters. Simple computational forms are shown to exist when SW and SNR are assumed known. An information-theoretic concept is used to extend these equations to the general case of SW and SNR unknown. A Monte Carlo simulation experiment is used to verify that the method can work, with no a priori information for either SW or SNR and a very small (20 pulse) sample size. The improved performance of this new Doppler velocity estimator is documented by comparison with derived optimal bounds and with the performance of the pulse pair (PP) method. Bayes estimator results are used to provide true performance bounds for comparison. Cramer-Rao bounds are also derived and shown to be inferior to the Bayes bounds in the small sample case considered     

一种基于小波与遗传算法的小目标检测算法

本文提出了一种快速检测序列图像中低信噪比(＜2)小目标的算法.该算法采用小波滤波器对每帧图像滤波,提高目标的信噪比,剔除部分噪声点,降低了低信噪比小目标检测算法的运算量;设计了基于遗传算法的起始航迹搜索算法,有效地避免航迹的漏检;采用截断序贯似然比检验,形成确认航迹.仿真结果表明应用此算法,可快速实现信噪比小于2的小目标(2×2)的检测与跟踪.     

Asymptotic efficiencies of truncated sequential tests

Truncation of a sequential test with constant boundaries is considered for the problem of testing a location hypothesis:f(x- theta_{0})versusf(x- theta_{1}). A test design procedure is developed by using bounds for the error probabilities under the hypothesis and alternative. By viewing the truncated sequential test as a mixture of a sequential probability ratio test and a fixed sample size test, its boundaries and truncation point can be obtained once the degree of mixture is specified. Asymptotically correct approximations for the operating characteristic function and the average sample number function of the resulting test are derived. Numerical results show that an appropriately designed truncated sequential test performs favorably as compared to both the fixed sample size test and the sequential probability ratio test with the same error probabilities. The average sample number function of the truncated test is uniformly smaller than that of the fixed sample size test, and the truncated test maintains average sample sizes under the hypothesis and the alternative that are close to those optimum values achieved by Wald's sequential probability ratio test. Moreover, the truncated test is more favorable than the sequential probability ratio test in the sense that is has smaller average sample size when the actual location parameter is betweentheta_{0}andtheta_{1}. This behavior becomes more pronounced as the error probabilities become smaller, implying that the truncated sequential test becomes more favorable as the error probabilities become smaller.     

低速短波非正交跳频网台信号分选技术研究

介绍了利用改进型的时间相关算法进行短波非正交跳频网台信号分选的方法。由于短波信号环境的复杂性,影响了对短波领域跳频信号的检测,使得跳频信号的持续时间这一关键技术参数无法正确获取,因此采取提高跳频信号检测的准确性和找回因"频率碰撞"而丢失的跳频频点等方法对时间相关分选算法进行改进,以提高网台信号分选的正确概率。通过实验分析,结果表明,在适当的信噪比条件下,改进型时间相关分选算法能够完成四部非正交跳频网台信号的分选,分选的正确率大大提高。     

The clipping loss in correlation detectors for arbitrary input signal-to-noise ratios

The detection of stationary Gaussian signals in a background of stationary Gaussian noise by the analog multiplier correlator, the polarity coincidence correlator (PCC), and the sample polarity coincidence correlator (SPCC) is considered. It is assumed that signal and noise have identical normalized autocovariance functions, and they are not cross correlated with each other. The main contributions of this paper are the exact expressions for the output signal-to-noise ratio (SNR) for the correlators mentioned for all values of the input SNR. It is shown that there exists a critical value of the input SNR, such that, whenever this value is exceeded, the PCC output SNR exceeds that of the analog correlator. A sufficient condition for this gain in output SNR is obtained in terms of the input SNR. This result is illustrated for stationary Gauss-Markov processes.     

动态大规模无线传感器网络决策融合

为了解决动态大规模无线传感器网络的决策融合问题,该文提出了一种表决决策融合规则。假设无线传感器网络中信道的衰减服从瑞利分布,传感器的数量服从泊松分布。在不同的系统参数下,对融合规则的检测性能进行了分析和仿真。结果表明,只要传感器的平均数量充分多,此融合规则即使在较低的信噪比下,也能提供良好的系统检测性能。并且与已有的非参数融合规则相比,此融合规则可以提供更好的检测性能。同时,通过使用决策融合系统的偏移系数,给出了传感器输出的最优接收阈值的获取方法。     

Throughput and packet error probability of cellularfrequency-hopped spread-spectrum radio networks

The authors characterize multiple-access interference for cellular mobile networks, in which users are assumed to be Poisson-distributed in the plane and use frequency-hopped spread-spectrum signaling with a transmitter-oriented assignment of frequency-hopping patterns. Exact expressions for the bit error probabilities are derived for binary coherently demodulated systems without coding. Approximations for the packet-error probability are derived for coherent and noncoherent systems and these approximations are applied when forward-error-control coding is used. In all cases, the effects of varying interference power are accurately taken into account according to some propagation law. Numerical results are given in terms of bit-error probability for the exact case and throughput for the approximate analyses. Comparisons are made with previously derived bounds, and it is shown that these tend to be very pessimistic     

一种基于小波变换的序列图像中小目标检测与跟踪算法

该文提出了一种快速检测序列图像中低信噪比(2dB)小目标的算法。采用小波滤波器对每帧图像滤波,提高目标的信噪比,降低了低信噪比小目标检测算法的运算量;采用固定长度的假设检验算法,生成起始航迹,有效地避免航迹的漏检;采用截断序贯似然比检验,形成确认航迹。仿真结果表明应用此算法,可快速实现信噪比小于2dB的小目标(22)的检测与跟踪。     

Performance analysis of LMS adaptive prediction filters

The conditions required to implement real-time adaptive prediction filters that provide nearly optimal performance in realistic input conditions are delineated. The effects of signal bandwidth, input signal-to-noise ratio (SNR), noise correlation, and noise nonstationarity are explicitly considered. Analytical modeling, Monte Carlo simulations and experimental results obtained using a hardware implementation are utilized to provide performance bounds for specified input conditions. It is shown that there is a nonlinear degradation in the signal processing gain as a function of the input SNR that results from the statistical properties of the adaptive filter weights. The stochastic properties of the filter weights ensure that the performance of the adaptive filter is bounded by that of the optimal matched filter for known stationary input conditions