Maximum likelihood blood velocity estimator incorporating properties of flow physics

The aspect of correlation among the blood velocities in time and space has not received much attention in previous blood velocity estimators. The theory of fluid mechanics predicts this property of the blood flow. Additionally, most estimators based on a cross-correlation analysis are limited on the maximum velocity detectable. This is due to the occurrence of multiple peaks in the cross-correlation function. In this study a new estimator (CMLE), which is based on correlation (C) properties inherited from fluid flow and maximum likelihood estimation (MLE), is derived and evaluated on a set of simulated and in vivo data from the carotid artery. The estimator is meant for two-dimensional (2-D) color flow imaging. The resulting mathematical relation for the estimator consists of two terms. The first term performs a cross-correlation analysis on the signal segment in the radio frequency (RF)-data under investigation. The flow physic properties are exploited in the second term, as the range of velocity values investigated in the cross-correlation analysis are compared to the velocity estimates in the temporal and spatial neighborhood of the signal segment under investigation. The new estimator has been compared to the cross-correlation (CC) estimator and the previously developed maximum likelihood estimator (MLE). The results show that the CMLE can handle a larger velocity search range and is capable of estimating even low velocity levels from tissue motion. The CC and the MLE produce incorrect velocity estimates due to the multiple peaks, when the velocity search range is increased above the maximum detectable velocity. The root-mean square error (RMS) on the velocity estimates for the simulated data is on the order of 7 cm/s (14%) for the CMLE, and it is comparable to the RMS for the CC and the MLE. When the velocity search range is set to twice the limit of the CC and the MLE, the number of incorrect velocity estimates are 0, 19.1, and 7.2% for the CMLE, CC, and MLE, respectively. The ability to handle a larger search range and estimating low velocity levels was confirmed on in vivo data.     

Maximum likelihood for target location in the presence of substitutive noise

We consider the optimal likelihood algorithm for the estimation of a target location when the images are corrupted by substitutive noise. We show the relationship between the optimal algorithm and the sliced orthogonal nonlinear generalized (SONG) correlation. The SONG correlation is based on the application of a linear correlation to corresponding binary slices of both the input scene and the reference object with appropriate weight factors. For a particular case, we show that the optimal strategy is a function of only the number of pixels for which the gray values in the noisy image match the ones of the reference image when the substitutive noise is uniformly distributed. This is exactly what a particular definition of the SONG correlation does.     

Maximum likelihood estimation techniques for concurrent flaw subpopulations

Failure of structural materials is often caused by the presence of two or more types of defect subpopulations. The maximum likelihood estimation technique for evaluating the Weibull parameters of these underlying subpopulations in the case of known fracture origin is presented. The maximum likelihood estimation equations are derived, and solved by means of nonlinear programming. The estimators obtained therefrom are tested for both accuracy and consistency against a series of simulation runs. For data sets containing a relatively small sample size, the advantage of the method of maximum likelihood over two established nonparametric techniques is demonstrated.     

Maximum likelihood estimation from record-breaking data for the weibull distribution

In destructive stress testing, industrial quality control, or other situations, data may consist only of record setting values, such as successive values that are smaller than all previous ones observed. Here, for a two-parameter Weibull distribution, the performance of the maximum likelihood estimators (MLEs) from record-breaking data is studied by computer simulations. Comparison of the biases and mean squared errors of these estimators with those of the MLEs for complete samples from the Weibull distribution is discussed and some examples are presented.     

非理想信道估计条件下OFDM系统的最大似然检测算法

基于最大似然的准则,研究了理想信道估计条件下和非理想信道估条件下OFDM系统的最优检测算法。研究结果表明,当发送信号为PSK调制方式时,无论是理想信道估计还是非理想信道估计,最大似然检测算法与传统的迫零检测算法等价。但当信道估计非理想且发送信号的调制方式为16QAM或高阶QAM时,采用最大似然检测算法才能够获得更好的性能。     

Maximum likelihood signal-to-noise ratio estimation for coded linearly modulated signals

In this study, the authors propose an exact maximum likelihood (ML) signal-to-noise ratio (SNR) estimator for coded linearly modulated signals. The estimator is expressed in terms of the marginal a posteriori probabilities (APPs) of the coded symbols, which can be obtained efficiently by the Bahl-Cocke- Jelinek-Raviv (BCJR) algorithm for codes defined on trellises. Simulation results show that the proposed ML code-aided (CA) SNR estimator significantly outperforms the non-data-aided (NDA) estimators in the low SNR regime. The Cramer-Rao bound (CRB) for CA SNR estimator is also derived and evaluated numerically. It is shown that the proposed ML-CA estimator performs very close to the derived bound. Comparisons of the CRBs for CA and NDA scenarios with different linearly modulated signals further illustrate the intrinsic performance improvement by exploiting the channel coding constraints.     

A non-parametric monotone maximum likelihood estimator of time trend for repairable system data

The trend-renewal process (TRP) is defined to be a time-transformed renewal process, where the time transformation is given by a trend function λ(·) which is similar to the intensity of a non-homogeneous Poisson process (NHPP). A non-parametric maximum likelihood estimator of the trend function of a TRP is obtained under the often natural condition that λ(·) is monotone. An algorithm for computing the estimate is suggested and examined in detail in the case where the renewal distribution of the TRP is a Weibull distribution. The case where one has data from several systems is also briefly studied.     

A weighted total least squares estimator for multivariable systemswith nearly maximum likelihood properties

The aim of the present paper is to develop a parametric estimator for linear time-invariant multivariable systems with nearly maximum likelihood properties. The estimator is based on the total least squares (TLS) method. It can be seen as an “optimally” weighted iterative generalized TLS (GTLS) estimator, combining the nice asymptotic properties of the maximum likelihood (ML) method with the global minimization property of the GTLS estimator     

Temperature controlled oven for low noise measurement systems [forelectromigration characterization]

Low-frequency noise (LFN) measurements are often applied to the characterization of electron devices. When such measurements have to be performed on electronic components maintained at a given temperature, the thermal stability of the oven which is used for this purpose becomes a major concern, because of the high sensitivity of electron devices to temperature fluctuations (TF's). In this paper, we present the realization of a high-stability temperature-controlled oven, purposely designed for the characterization of electromigration in metal interconnections of integrated circuits by means of low-frequency noise measurements. The prototype which has been realized demonstrates that the contribution of the thermal fluctuations of the oven to the background noise of the measurement system is negligible down to frequencies as low as 10 mHz in the entire range of operating temperatures (25-250°C)     

Maximum likelihood estimation of change point from stationary to nonstationary in autoregressive models using dynamic linear model

Change point estimation is a useful concept in time series models that could be applied in several fields such as financing, quality control. It helps to decrease costs of decision making and production by monitoring stock market and production lines, respectively. In this paper, the maximum likelihood technique is developed to estimate change point at which the stationary AR(1) model changes to a nonstationary process. Filtering and smoothing of dynamic linear model are used to estimate unknown parameters after change point. We also assume that correlation exists between samples' statistics. Simulation results show the effectiveness of the proposed estimators to estimate the change point of stationary. In addition based on Shewhart control chart, filtering has a better accuracy in comparison to smoothing. A real example is provided to illustrate the application.     

Penalized likelihood ratio tests for repeated measurement models

In this paper, we propose a novel test procedure for repeated measurements based on the penalized likelihood ratio (PLR). The procedure provides an alternative to the standard likelihood ratio tests for evaluating null hypotheses concerning the correlation structure of repeated measurements. PLR tests are specifically designed for nonstandard test situations where non-identifiability of a nuisance parameter occurs under the null hypothesis. The idea is to penalize the estimation close to the boundary of the domain of the nuisance parameter and thereby eliminate the non-identifiability. We show that the asymptotic distribution of the PLR test is a 50:50 mixture of chi-square distributions with 0 and 1 degrees of freedom. Simulation studies indicate that the asymptotic distribution of the PLR test provides a good approximation, even for fairly small data sets (10–20 subjects). A sensitivity analysis with a real data example highlights the strengths and weaknesses of the test procedure.     

Minimum density power divergence estimator for GARCH models

In this paper, we study the robust estimation for the generalized autoregressive conditional heteroscedastic (GARCH) models with Gaussian errors. As a robust estimator, we consider a minimum density power divergence estimator (MDPDE) proposed by Basu et al. (Biometrika 85:549–559, 1998). It is shown that the MDPDE is strongly consistent and asymptotically normal. Our simulation study demonstrates that the MDPDE has robust properties in contrast to the maximum likelihood estimator. A real data analysis is performed for illustration.     

A new wideband spread target maximum likelihood estimator for blood velocity estimation. II. Evaluation of estimator with experimental data

For pt.I see ibid., vol.38, p.1-16, Jan. 1991. The signal models and performance of the estimation strategies described in pt.I are tested with experimental ultrasonic data. The ultrasonic data analyzed verify the theoretical model and predicted performance. The averaged correlation, verified experimentally, confirms that the correlation envelope can be used to estimate the velocity of scatterers and that the shape of the correlation function conveys information regarding the velocity profile within the sample volume. For both the wideband point and range spread estimators, the predicted improvement in velocity resolution and the reduction in height of subsidiary velocity peaks are demonstrated. Through the use of these estimation strategies, information regarding the mean velocity and velocity variation are available for each spatial location within the vessel. This information is presented using a three-dimensional spatial velocity profile display, which appears to offer a number of advantages in the rapid identification of pathology.     

A new wideband spread target maximum likelihood estimator for blood velocity estimation. I. Theory

The derivation and theoretical evaluation of new wideband maximum-likelihood strategies for the estimation of blood velocity using acoustic signals are presented. A model for the received signal from blood scatterers, using a train of short wideband pulses, is described. Evaluation of the autocorrelation of the signal based on this model shows that the magnitude, periodicity, and phase of the autocorrelation are affected by the mean scatterer velocity and the presence of a velocity spread target. New velocity estimators are then derived that exploit the effect of the scatterer velocity on both the signal delay and the shift in frequency. The wideband range spread estimator is derived using a statistical model of the target. Based on the point target assumption, a simpler wideband maximum-likelihood estimator is also obtained. These new estimation strategies are analyzed for their local and global performance. Evaluation of the Cramer-Rao bound shows that the bound on the estimator variance is reduced using these estimators, in comparison with narrowband strategies. In order to study global accuracy, the expected estimator output is evaluated, and it is determined that the width of the mainlobe is reduced. In addition, it is shown that the height of subsidiary velocity peaks is reduced through the use of these new estimators.     

A maximum likelihood estimator for linear and nonlinear systems-apractical application of estimation techniques in measurement problems

A method is presented for estimating the parameters of linear systems and nonlinear systems. The linear systems are modeled by their transfer function, while the nonlinear systems are described by a Volterra series. The estimator belongs to the class of maximum-likelihood estimators. During the estimation process, the Cramer-Rao lower bound on the covariance matrix of the estimates is derived     

Joint design of optimum partial response target and equalizer for recording channels with jitter noise

We address joint design of optimum generalized partial response (GPR) target and equalizer for perpendicular recording channels with jitter noise. We develop a new cost function which accounts for the data-dependent nature of jitter noise based on the minimum mean square error (MMSE) criterion. Using the step-response-based channel model, we derive expressions for the statistics required to compute the optimum equalizer and target in the presence of jitter noise. We also derive a bit-response-based model for the jitter noise channel. We present an approach for doing simulations as well as analytical computations for the jitter noise channel without resorting to the widely used Taylor series approximations. Our computational and simulation results show that, while the targets designed without accounting for the jitter lead to error-floor effect in the bit-error-rate performance, the targets designed by our approach give significant performance improvement under high jitter conditions, with no sign of error-floor effect for the range of signal-to-noise ratios considered.     

Maximum likelihood estimation of A-scan amplitudes for coherent targets in media of unresolvable scatterers

The author derives a maximum-likelihood estimator (MLE) for A-scan amplitudes corresponding to coherent reflectors embedded in media of unresolvable scatterers. The MLE processes sampled RF A-scans from broadband ultrasonic pulse-echo systems. A major source of interference for these signals is the backscattered energy from the unresolvable scatterers that exist throughout the beam field. A statistical model is formulated that characterizes the backscattered energy from a resolution cell when a coherent target scatterer is present. It is shown that the MLE is equivalent to a matched filter when the distribution of the interfering back-scatter energy is stationary over the resolution cell. In addition, the form of the MLE is described when the interfering echoes are not stationary within the resolution cell. Experimental results are presented for an adaptive implementation of the MLE applied to flaw detection in stainless steel. The results demonstrate the ability of the MLE to reveal targets masked by grain echoes, without prior knowledge of the gain-echo spectral characteristics.     

海洋环境噪声的一般模型及声压空间相关系数

1引言海洋环境噪声是声纳设备的重要干扰之一,它的存在降低了声纳的检测能力。水听器阵信噪比增益一直是水声学研究的重要问题,而阵增益与噪声的相关特性密切联系,因此,研究噪声的时空相关特     

Maximum fiber coupling efficiency and optimum beam size in the presence of random angular jitter for free-space laser systems and their applications

Free-space laser communication systems use optical-fiber-based technology such as optical amplifiers, receivers, and high-speed modulators. In these systems using single-mode fibers, the fiber coupling efficiency is one of the most significant issues to be solved. Optimum relationships between a focused optical beam and mode field size of the optical fiber in the presence of random angular jitter are discussed in relation to fiber-coupled optical systems. Maximum fiber coupling efficiency is analytically derived with the optimum Airy disk radius normalized by the mode field radius as a function of random angular jitter. The fade level of fiber-coupled signals at desired fade probability is investigated. It is shown that the average bit error ratio significantly degrades with the random angular jitter normalized by the mode field radius larger than about 0.3 when the Airy disk size is optimally selected.