能量和功率在分析跨区域模态中的现象时的应用

这篇论文提出了一种基于能量的小信号方法,用以分析区域间的低频振荡。在对电力系统线性模型中能量关系分析的基础上,一个全面的分析系统振荡的方法框架被建立起来。这种方法可以使我们深入的了解区域间现象的性质,也可以和现代技术结合起来进行复杂电力系统的频谱分析。     

A cross-reference method of parameter estimation and noise reduction and its applications

This paper proposes a cross-reference method of nonlinear time series analysis, combining the tasks of dynamical system parameter estimation and noise reduction which were fulfilled separately before. With the positive interaction between the two processing modules, the method is somewhat superior. Some prior works can be viewed as special cases of this general framework and effective new algorithms may be devised according to it. Two examples of chaotic time series analysis are also given to show the applicability of the proposed method.     

用于盲接收的turbo均衡与迭代信道估计

Turbo均衡是一种将信道均衡和差错控制译码联合迭代处理的均衡机制,与传统的均衡器相比,能在更低的信噪比条件下克服严重信道失真导致的符号间干扰(ISI)。该文提出一种用于盲接收的turbo均衡和迭代信道估计方案,不依赖于训练序列或发送符号的先验知识,采用初始盲均衡处理来启动迭代信道估计和turbo均衡。在该方案中,初始盲均衡算法的选择是十分关键的,它需要在恶劣的信道条件为后续迭代处理的启动提供足够的先验信息。该文根据turbo均衡的特点,选择了超指数算法作为初始盲均衡。仿真结果表明,该文提出的用于盲接收的turbo均衡方案是有效的。     

中继信道相位响应模型及其估计算法研究

中继能够提高信息传输质量及覆盖区域,是一种近年来得到迅速发展且前景广阔的无线通信技术。而性能优良的中继信道估计构成了改善通信环境的其他技术的基础前提。针对中继信道估计中的相位响应部分,首先建立了在任意信噪比条件下的相位噪声模型。考虑到估计过程快速的现实要求,通过将模型中原有复杂的表达噪声形式用高斯的方法近似化,得到了较为简洁的结果,并根据不同的简化形式给出对应的若干相位响应估计算法。为了比较这些算法之间的性能,重点推导了估计算法所能达到的CRLB。最后结合计算机数值仿真验证了结论的正确性。     

Distributed multichannel speech enhancement with minimum mean-square error short-time spectral amplitude, log-spectral amplitude, and spectral phase estimation

In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time spectral amplitude (STSA), log-spectral amplitude (LSA), and spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products.     

相位恢复算法:原理、发展与应用（特邀）

研究表明,由于相位比振幅包含更多关于场的信息,因此相位测量在现代科学和工程的诸多分支中始终是研究的热点问题。在可见的电磁波范围内,相位信息很难通过现有的光电探测器直接采集获取。相位恢复技术提供了一种从捕获的强度信息中将相位信息“计算”出来的有效手段,并已成功应用于天文观测、生物医学成像和数字信号复原等多个科学领域。算法是相位恢复技术的核心,也是该技术发展和应用的关键。文中结合物理学原理和信号处理方法对相位恢复算法的基本原理进行阐述,综述了各类相位恢复算法的发展历程及其优缺点,并简单概述了相位恢复算法在光学领域的典型应用,最终指明其面临的挑战和未来的发展趋势:更优异的收敛性能和噪声鲁棒性、恢复更复杂物体相位信息的能力、多目标多任务集成的兼容性。     

Simultaneous estimation of heat transfer coefficient and thermal conductivity with application to microelectronic materials

An estimation of unknown properties of materials arises naturally when one considers some aspects of thermal modeling, especially carried out by widely used numerical methods, e.g. Finite Element Method (FEM).We propose a new approach of simultaneous thermal conductivity and heat transfer coefficient estimation based on thermographic measurements. A linear, steady-state distributed parameter model is used in order to describe the test sample. Thermal properties measurement is equivalent to the unknown parameter estimation of this system. The proposed method is practically applied for estimation of thermal conductivity and heat transfer coefficient of thick-film modules made on alumina (96% Al₂O₃) and DP951 ceramic substrates. In these experiments a high-resolution thermographic scanner is used.The obtained results for thermal conductivity and heat transfer factor are fully comparable with previously published ones.     

WCDMA中Turbo码算法及质数交织器的研究

介绍了WCDMA中所采用的Turbo码编码结构中、质数交职器、MAP解码算法，进而给出不同内交织结构下，基于MAP算法的Turbo码译码性能仿真曲线与相关结论。     

通向信道编码定理的Turbo码及其性能分析

本文综述了Shannon编码定理指导下信道编、译码的发展概况及趋势。全面、系统地分析了最近引起普遍强烈关注的Turbo码的基本构造原理和其能够达到惊人的优异性能的原因.指出了目前该领域些很有理论价值与应用意义的研究方向.     

Parameter estimation based on fractional power spectrum under alpha-stable distribution noise environment in wideband bistatic MIMO radar system

This paper takes the alpha-stable distribution as the noise model and works on the parameter estimation problem of wideband bistatic Multiple-Input Multiple-Output (MIMO) radar system in the impulsive noise environment. In many applications, it is not appropriate to approximate the wideband signal by the narrowband model. Furthermore, the echo signal may be corrupted by the non-Gaussian noise. The conventional algorithms degenerate severely in the impulsive noise environment. Thus, this paper proposes a new wideband signal model and a novel method in wideband bistatic MIMO radar system. It combines the fractional lower order statistics and fractional power spectrum, for suppressing the impulse noise and estimating parameters of the target. Firstly, a new signal array model is proposed under the alpha-stable distribution noise model. Secondly, Doppler stretch and time delay are jointly estimated by peak searching of the FLOS-FPSD. Furthermore, two modified algorithms are proposed for the estimation of the direction-of-departure and direction-of-arrival, including the fractional power spectrum density based on MUSIC algorithm (FLOS-FPSD-MUSIC) and the fractional lower-order ambiguity function based on ESPRIT algorithm (FLOS-FPSD-ESPRIT). Simulation results are presented to verity the effectiveness of the proposed method.     

Robust spatial time-frequency distribution matrix estimation with application to direction-of-arrival estimation

We consider the problem of estimating spatial time-frequency distribution (STFD) matrices in the presence of impulsive noise. STFD matrices are widely used in sensor array processing for direction-of-arrival estimation and blind source separation of non-stationary sources. Conventional methods fail when the noise is non-Gaussian or impulsive. We propose robust techniques for STFD estimation which are based on pre-processing, robust position based estimation and robust covariance based estimation. The proposed methods are compared in terms of direction-of-arrival estimation performance.     

Application of natural computing algorithms to maximum likelihood estimation of direction of arrival

This work presents a study of the performance of populational meta-heuristics belonging to the field of natural computing when applied to the problem of direction of arrival (DOA) estimation, as well as an overview of the literature about the use of such techniques in this problem. These heuristics offer a promising alternative to the conventional approaches in DOA estimation, as they search for the global optima of the maximum likelihood (ML) function in a framework characterized by an elegant balance between global exploration and local improvement, which are interesting features in the context of multimodal optimization, to which the ML-DOA estimation problem belongs. Thus, we shall analyze whether these algorithms are capable of implementing the ML estimator, i.e., finding the global optima of the ML function. In this work, we selected three representative natural computing algorithms to perform DOA estimation: differential evolution, clonal selection algorithm, and the particle swarm. Simulation results involving different scenarios confirm that these methods can reach the performance of the ML estimator, regardless of the number of sources and/or their nature. Moreover, the number of points evaluated by such methods is quite inferior to that associated with a grid search, which gives support to their application.     

Sparse least mean mixed‐norm adaptive filtering algorithms for sparse channel estimation applications

Sparse least‐mean mixed‐norm (LMMN) algorithms are developed to improve the estimation performance for sparse channel estimation applications. Both the benefits of the least mean fourth and least mean square algorithms are utilized to exploit a type of sparse LMMN algorithms. The proposed sparse‐aware LMMN algorithms are implemented by integrating an l ₁‐norm or log‐sum function into the cost function of traditional LMMN algorithm so that they can exploit the sparse properties of the broadband multi‐path channel and achieve better channel estimation performance. The proposed sparse LMMN algorithms are equal to adding an amazing zero‐attractor in the update equation of the traditional LMMN algorithm, which aim to speed up the convergence. The channel estimation performance of the proposed sparse LMMN algorithms are evaluated over a sparse broadband multi‐path channel to verify their effectiveness. Simulation results depict that the sparse LMMN algorithms are superior to the previously reported sparse‐aware least mean square/fourth, least mean fourth and least mean square and their corresponding sparse‐aware algorithms in terms of both the convergence and steady‐state behavior when the broadband multi‐path channel is sparse. Copyright © 2016 John Wiley & Sons, Ltd.     

图像边缘检测算法的比较分析

随着社会的快速发展,图像边缘检测的方法也逐步的多样化,为了能够全面提升其图像边缘检测的效率,需要对整体的检测方法进行全面的创新.但在实际的检测过程中,其检测环境还相对复杂,导致边缘检测的难度相对较大.所以,对检测法进行优化十分关键.本文主要针对图像边缘检测法进行比较分析.并提出了相应的优化措施.     

一种波达方向、频率联合估计快速算法

首先提出了基于PM(propagator method)方法的波达方向(DOA)、频率联合估计快速算法，给出了PM算子的一个估计，由PM算子构造出一特殊的低维矩阵，其特征值给出频率的估计，进而由估计的频率和相应的特征矢量得到DOA的估计。该算法具有参数自动配对，计算量小的优点，易于在工程应用中实时处理。计算机仿真结果证实了算法的有效性。     

A CLOSED-FORM WIDEBAND DIRECTION-OF-ARRIVAL ESTIMATION WITH CHIRPLET-BASED ADAPTIVE SIGNAL DECOMPOSITION ALGORITHM

The Direction-Of-Arrival (DOA) estimation with Coherent Signal Subspace (CSS)is not easy to cxtend from narrowband to wideband case.Time-frequency analysis is a powerfultechnique to deal with time-variant or non-stationary signal. Its combination with CSS exploresa new field in signal processing, especially the wideband DOA estimation. The chirp function isone of the most fundamental functions in nature. Many nature events can be modeled as chirpletfunction, such as radar system or scismic exploring.Hence,the chirplet-based signal decomposi-     

A new approach to power estimation and reduction in CMOS digital circuits

Modelling and optimization of dynamic capacitive power consumption in digital static CMOS circuits, taking into consideration a reason of a gate switching—gate control mode, is discussed in the present paper. The term ‘gate control mode’ means that a number and type of signals applied to input terminals of the gate have an influence on total amount of energy dissipated during a single switching cycle. Moreover, changes of input signals, which keep the gate output in a steady state, can also cause power consumption. Based on this observation, complex reasons of power losses have been considered. In consequence, the authors propose a new model of dynamic power consumption in static CMOS gates. Appropriate parameters’ calculation method for the new model was developed. The gate power model has been extended to logic networks, and consequently a new measure of the circuit activity was proposed. Switching activity, which is commonly used as a traditional measure, characterizes only the number of signal changes at the circuit node, and it is not sufficient for the proposed model. As the power consumption parameters of CMOS are dependent on their control mode, the authors used probability of the node control mode as a new measure of the circuit activity. Based on the proposed model, a procedure of combinational circuit optimization for power dissipation reduction has been developed. The procedure can be included in a design flow, after technology mapping. Results of the power estimation received for some benchmark circuits are much closer to SPICE simulations than values obtained for other methods. So the model proposed in this study improves the estimation accuracy. Additionally, we can save several percent of the consumed energy.     

Learning characteristics of stochastic-gradient-descent algorithms: A general study,analysis, and critique

A comprehensive analysis of the mean-square learning characteristics of stochastic-descent algorithms is presented. The approach is based on the commonly exploited simplifying assumption of stationary independent training vectors. Characteristics analyzed include stability, steady-state misadjustment, initial rate of convergence, optimum step size, and steady-state autocovariance and spectral characteristics of the weight-vector. Effects on these characteristics due to degree of randomness of stochastic gradient, particular data distribution, and data corruption are isolated and analyzed. An objective of the work is to keep the number of simplifying assumptions and approximations to a minimum. Comparison of results with previous more approximate analyses are made.     

Robust energy-to-peak sideslip angle estimation with applications to ground vehicles

In this paper, the observer design problem for the sideslip angle of ground vehicles is investigated. The sideslip angle is an important signal for the vehicle lateral stability, which is not measurable by using an affordable physical sensor. Therefore, we aim to estimate the sideslip angle with the yaw rate measurements by employing the vehicle dynamics. The nonlinear lateral dynamics is modeled firstly. As the tyre model is nonlinear and the road adhesive coefficient is subject to a large variation, the nonlinear lateral dynamics is transformed into an uncertain model. Considering the variation of longitudinal velocity, an uncertain linear-parameter-varying (LPV) system is obtained. Based on the LPV model, a gain-scheduling observer is proposed and the observer gain can be determined with off-line computation and on-line computation. The off-line computation includes the calculation of a set of linear matrix inequalities and the on-line computation contains several algebraic operations. The proposed design methodology is applied to a four-wheel-independent-drive electric vehicle in simulation. It infers from different maneuvers that the designed observer has a good performance on estimating the sideslip angle.