End-to-end color printer calibration by total least squaresregression

Neugebauer (1937) modeling plays an important role in obtaining end-to-end device characterization profiles for halftone color printer calibration. This paper proposes total least square (TLS) regression methods to estimate the parameters of various Neugebauer models. Compared to the traditional least squares (LS) based methods, the TLS approach is physically more appropriate for the printer modeling problem because it accounts for errors in the measured reflectance of both the primaries and the modeled samples. A TLS method based on print measurements from single-colorant step-wedges is first developed. The method is then extended to incorporate multicolorant print measurements using an iterative algorithm. The LS and TLS techniques are compared through tests performed on two color printers, one employing conventional rotated halftone screens and the other using a dot-on-dot halftone screen configuration. Our experiments indicate that the TLS methods yield a consistent and significant improvement over the LS-based techniques for model parameter estimation. The gains from the TLS method are particularly significant when the number of patches for which measured data is available is limited.     

Formulation and solution of structured total least norm problemsfor parameter estimation

The total least squares (TLS) method is a generalization of the least squares (LS) method for solving overdetermined sets of linear equations Ax≈b. The TLS method minimizes ∥[E|-r]∥_F, where r=b-(A+E)x, so that (b-r)∈Range (A+E), given A∈C^m×n, with m⩾n and b∈C^m×1. The most common TLS algorithm is based on the singular value decomposition (SVD) of [A/b]. However, the SVD-based methods may not be appropriate when the matrix A has a special structure since they do not preserve the structure. Previously, a new problem formulation known as structured total least norm (STLN), and the algorithm for computing the STLN solution, have been developed. The STLN method preserves the special structure of A or [A/b] and can minimize the error in the discrete L_p norm, where p=1, 2 or ∞. In this paper, the STLN problem formulation is generalized for computing the solution of STLN problems with multiple right-hand sides AX≈B. It is shown that these problems can be converted to ordinary STLN problems with one right-hand side. In addition, the method is shown to converge to the optimal solution in certain model reduction problems. Furthermore, the application of the STLN method to various parameter estimation problems is studied in which the computed correction matrix applied to A or [A/B] keeps the same Toeplitz structure as the data matrix A of [A/B], respectively. In particular, the L₂ norm STLN method is compared with the LS and TLS methods in deconvolution, transfer function modeling, and linear prediction problems     

Constrained maximum likelihood solution of linear equations

The total least squares (TLS) is used to solve a set of inconsistent linear equations Ax≈y when there are errors not only in the observations y but in the modeling matrix A as well. The TLS seeks the least squares perturbation of both y and A that leads to a consistent set of equations. When y and A have a defined structure, we usually want the perturbations to also have this structure. Unfortunately, standard TLS does not generally preserve the perturbation structure, so other methods are required. We examine this problem using a probabilistic framework and derive an approach to determining the most probable set of perturbations, given an a priori perturbation probability density function. While our approach is applicable to both Gaussian and non-Gaussian distributions, we show in the uncorrelated Gaussian case that our method is equivalent to several existing methods. Our approach is therefore more general and can be applied to a wider variety of signal processing problems     

Total least squares phased averaging and 3-D ESPRIT for jointazimuth-elevation-carrier estimation

The method of total least squares (TLS) phased averaging for high-performance subspace fitting in the three-dimensional (3-D) case of spectral estimation with 3-D ESPRIT is introduced and applied to the joint azimuth elevation-carrier estimation problem with two-dimensional (2-D) uniform rectangular arrays. The method is highly efficient computationally and is suitable for large arrays. Detailed computer experiments and comparisons are provided. For a 16×16 array of sensors and heavy noise, TLS phased-averaging 3-D ESPRIT exceeds the 3-D TLS unitary ESPRIT estimator by 300% in RMSE performance     

Performance analysis of the total least squares ESPRIT algorithm

The asymptotic distribution of the estimation error for the total least squares (TLS) version of ESPRIT is derived. The application to a uniform linear array is treated in some detail, and a generalization of ESPRIT to include row weighting is discussed. The Cramer-Rao bound (CRB) for the ESPRIT problem formulation is derived and found to coincide with the asymptotic variance of the TLS ESPRIT estimates through numerical examples. A comparison of this method to least squares ESPRIT, MUSIC, and Root-MUSIC as well as to the CRB for a calibrated array is also presented. TLS ESPRIT is found to be competitive with the other methods, and the performance is close to the calibrated CRB for many cases of practical interest. For highly correlated signals, however, the performance deviates significantly from the calibrated CRB. Simulations are included to illustrate the applicability of the theoretical results to a finite number of data     

Localization of sensitive areas of power AC switch under thermal laser stimulation

Thermal laser stimulation (TLS) is a widely used tool in a failure analysis laboratory to detect defects in integrated circuits. TLS can also be used for good device characterization. In this paper, we apply TLS – and especially optical beam induced resistance change (OBIRCH) method – to localization of electrically high stressed areas. We test this process with a new product from power AC switch family without failure. We localize several sensitive areas involved during and after switching, which are similar to the ones obtained by electrical simulations.     

Localization of wideband signals using least-squares and totalleast-squares approaches

In this paper, we introduce a new focusing technique for localization of wideband signals. Relaxing the unitary assumption for the focusing matrices, we formulate the least-square (LS) and the total least-square (TLS) coherent signal-subspace methods. The TLS is an alternative to the conventional LS and uses the fact that errors can exist both in the focusing location matrix as well as in the estimated location matrix at a given frequency bin. To prevent the focusing loss, we use a class of focusing matrices that are constant under multiplication by their Hermitian transpose. The class of unitary matrices comports with this property. We then develop a new focusing technique based on a modification to the TLS (MTLS). It is shown that the computational complexity of the new technique is significantly lower than that for the rotational signal subspace method (RSS). The focusing gain of the new technique is also larger than the focusing gain of the RSS algorithm. The simulation study shows that, compared with the RSS, the new algorithm has a smaller resolution signal to-noise ratio (SNR)     

基于宽窄带脉冲结合的运动估计方法

文中为机动目标提出了一种宽带和窄带脉冲相结合的雷达运动参数估计方法。该方法采用相邻脉冲互相关法(CCAE)作为宽带估计方法,采用基于牛顿迭代的最大似然估计方法(MN)作为窄带估计方法。文中提出的融合方法具有两个优点。首先,融合方法利用CCAE的速度估计值作为MN方法的初始速度。由于CCAE的速度无模糊范围较大,能有效解决MN方法的速度模糊问题。其次,由于MN方法的距离和速度的估计精度对于初始加速度不敏感,该融合方法将CCAE的加速度估计值作为MN方法的最终加速度,把MN方法的三维搜索简化成二维搜索。分析了CCAE和MN方法的估计性能,并且比较了CCAE、MN方法和融合算法的计算复杂度。仿真结果表明:提出的宽窄带融合估计方法在距离和速度上拥有与MN方法相近的估计性能,并且拥有更低的计算量。     

Deconvolution and total least squares in finding the impulseresponse of an electromagnetic system from measured data

Total least squares (TLS) is a method of solving over-determined sets of linear equations AX≈b when there are errors both in the observation vector b(m×1) and in the data matrix A(m×n). This method is particularly useful when the data matrix A is singular or highly ill conditioned. We present the method of finding the TLS by applying the singular value decomposition to the discrete deconvolution problem. Numerical results are presented for finding the impulse response of a transmission line from experimental data. The advantage of this approach is that this method can be automated based on the signal to noise ratio of the measured data     

Fast and rigorous use of thermal time constant to characterize back end of the line test structure in advanced technology

Thermal time constant analysis (TTC) opens a wide range of applications: structure identification, 3D localization for very deep micron technologies. In this paper, we describe a new analysis methodology for TTC signatures induced by modulated thermal laser stimulation (TLS). Previous approaches did not allow a fast and rigorous method to acquire and treat transient TLS signals. To overcome these limitations we have done a theoretical study, based on the Fourier transform of an analytical model describing temporal dependency of the TLS signal, which is powerful for signature interpretation. This analysis flow is applied to 65 nm reliability test structure.     

一种抗冲击噪声的对数总体最小二乘自适应滤波算法

在未知系统输入信号和输出信号均含有噪声的环境中,传统的自适应滤波算法,如最小均方(LMS)算法,会产生有偏估计.总体最小二乘(TLS)算法能够同时最小化输入信号与输出信号的噪声干扰,是解决此类问题的重要方法.然而,在许多实际应用中,干扰噪声可能具有冲击特性,这使得传统基于2阶统计量的自适应滤波算法,包括总体最小二乘算法...     

Errors-in-variables modeling in optical flow estimation

Gradient-based optical flow estimation methods typically do not take into account errors in the spatial derivative estimates. The presence of these errors causes an errors-in-variables (EIV) problem. Moreover, the use of finite difference methods to calculate these derivatives ensures that the errors are strongly correlated between pixels. Total least squares (TLS) has often been used to address this EIV problem. However, its application in this context is flawed as TLS implicitly assumes that the errors between neighborhood pixels are independent. In this paper, a new optical flow estimation method (EIVM) is formulated to properly treat the EIV problem in optical flow. EIVM is based on Sprent's (1966) procedure which allows the incorporation of a general EIV model in the estimation process. In EIVM, the neighborhood size acts as a smoothing parameter. Due to the weights in the EIVM objective function, the effect of changing the neighborhood size is more complex than in other local model methods such as Lucas and Kanade (1981). These weights, which are functions of the flow estimate, can alter the effective size and orientation of the neighborhood. In this paper, we also present a data-driven method for choosing the neighborhood size based on Stein's unbiased risk estimators (SURE).     

Authenticated Confidential Channel Establishment and the Security of TLS-DHE

Transport Layer Security (TLS) is the most important cryptographic protocol in use today. However, finding a cryptographic security proof for the complete, unaltered protocol has proven to be a challenging task. We give the first such proof in the standard model for the core cryptographic protocol underlying TLS cipher suites based on ephemeral Diffie–Hellman key exchange (TLS-DHE). This includes the cipher suite TLS_DHE_DSS_WITH_3DES_EDE_CBC_SHA, which is mandatory in TLS 1.0 and TLS 1.1. It is impossible to prove the TLS Handshake secure in the classical security models of Bellare–Rogaway and Canetti–Krawczyk. The reason for this is that the final Finished messages of the TLS Handshake are encrypted with the session key, which provides an opportunity to distinguish real keys from random values. Therefore we start with proving the security of a truncated version of the TLS Handshake protocol, which has also been considered in previous work on TLS, and give the first proof of this variant in the standard model. Then we define the new notion of authenticated and confidential channel establishment (ACCE), which allows the monolithic analysis of protocols for which a modular security proof is not possible. We show that the combination of the TLS-DHE Handshake protocol and the TLS Record Layer encryption is secure in this model. Since the conference publication of this paper, the notion of ACCE has found many further applications, for example to the analysis of further TLS cipher suites (Krawczyk et al., Crypto 2013; Li et al., PKC 2014), advanced mechanisms like secure renegotiation of TLS session keys (Giesen et al., CCS 2013), and other practical protocols like EMV channel establishment (Brzuska et al., CCS 2013), SSH (Bergsma et al., CCS 2014), and QUIC (Lychev et al., S&P 2015).     

Nonlinear autoregressive and nonlinear autoregressive moving average model parameter estimation by minimizing hypersurface distance

The least squares (LS) can be used for nonlinear autoregressive (NAR) and nonlinear autoregressive moving average (NARMA) parameter estimation. However, for nonlinear cases, the LS results in biased parameter estimation due to its assumption that the independent variables are noise free. The total least squares (TLS) is another method that can used for nonlinear parameter estimation to increase the accuracy of the LS because it specifically accounts for the fact that the independent variables are noise corrupted. TLS has its own limitations, however, mainly because it is difficult for the method to isolate noise from the signal components. We present a new method that is based on minimization of hypersurface distance for accurate parameter estimation for NAR and NARMA models. Computer simulation examples show that the new method results in far more accurate NAR and NARMA model parameter estimates than do either the LS and TLS, with noise that is either white or colored, and retains its high accuracy even when the signal-to-noise ratio (SNR) is as low as 10 dB.     

Relationship Between Geometric Translations and TLS Estimation Bias in Bearings-Only Target Localization

This paper analyzes the effects of local coordinate translations and rotations on the bias and mean-squared error performance of the total least squares (TLS) bearings-only target localization algorithm. The TLS estimator was originally proposed to alleviate the severe bias problems associated with the traditional pseudolinear estimator. An interesting property of the TLS estimator, which is not shared by the pseudolinear estimator, is that its bias is sensitive to where the origin of the local Cartesian coordinates is placed. The paper provides a formal proof of this observation, discusses its implication on bias minimization, and proposes a simple and effective method for TLS bias reduction. The findings of the paper are illustrated with comprehensive simulation examples.     

Image denoising using total least squares.

In this paper, we present a method for removing noise from digital images corrupted with additive, multiplicative, and mixed noise. An image patch from an ideal image is modeled as a linear combination of image patches from the noisy image. We propose to fit this model to the real-world image data in the total least square (TLS) sense, because the TLS formulation allows us to take into account the uncertainties in the measured data. We develop a method to reduce the contribution from the irrelevant image patches, which will sharpen the edges and reduce edge artifacts at the same time. Although the proposed algorithm is computationally demanding, the image quality of the output image demonstrates the effectiveness of the TLS algorithms.     

一种新的波达方向估计子空间算法研究

MUSIC算法是一种属于特征结构的子空间超分辨方法。该算法性能优良,但需要进行矩阵特征分解,运算量大。对波达方向估计问题进行了研究并提出了一种新的子空间算法。该算法利用总体最小二乘（TLS）方法取代特征分解得到噪声子空间,运算复杂度低于MUSIC算法,使其实时实现成为可能。总体最小二乘处理减轻了噪声的影响,该算法性能与MUSIC算法相当。理论分析和计算机仿真结果表明此方法是有效的。     

A Proactive mobile‐initiated fast handoff scheme using the multihomed approach

Mobile IP (MIP) defines a mobility management for mobile users to continuously access data when the currently attachment is changed to another network. However, when mobile node (MN) roams between network segments, the handoff latency results in packet losses and transmission delay. In this paper, we propose a multihomed fast handoff scheme (MFH‐MIP) to decrease the handoff cost. In the proposed MFH‐MIP scheme, each MN is implemeted with the link layer trigger and multihomed techniques. Based on the link layer trigger, MN can collect signal strengths of nearby access points (APs) and switch to a new link automatically when the old link becomes unsuitable to connect. Using the multihomed technique, MN can prepare for handoff using two (or more) interfaces, in which (i) one is connected with the old link to receive packets and (ii) the other one is used to access nearby APs and select the most suitable one as the new link, in parellel. In this way, MN can continuously transmit and receive packets during handoff. Based on the proposed method, MN can roam smoothly among different networks in the wireless environment. Copyright © 2008 John Wiley & Sons, Ltd.     

一种三维刚体运动参数鲁棒估计的神经算法

该文提出一种基于特征点匹配的刚体运动参数估计方法。在运动估计线性算法的基础上,文中利用全最小二乘(TLS)方法来进行求解,并建立次分量提取神经元来获得该全最小二乘解。基于测量数据中出格点(Outlier)的存在,我们在神经元的权值学习规则中引入鲁棒估计思想。实验结果表明,该方法能有效地克服出格点产生的误差,准确地估计出刚体的三维运动参数,比较令人满意。     

基于TLS的相控阵雷达目标角度截获方法

本文提出了一种在相控阵雷达中利用总体最小二乘(TLS)估计进行目标角度截获,提取目标角度信息的方法.该方法不仅考虑了线性模型中观测向量的噪声扰动,而且考虑了数据矩阵中的噪声扰动,采用TLS估计的角度截获方法可以使包括观测向量误差和数据矩阵误差在内的误差矩阵达到Frobenius范数的最小值.