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。     

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.     

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。     

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.     

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.     

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 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.     

Adaptive reduced-rank LCMV beamforming algorithms based on joint iterative optimization of filters: Design and analysis

This paper presents reduced-rank linearly constrained minimum variance (LCMV) beamforming algorithms based on joint iterative optimization of filters. The proposed reduced-rank scheme is based on a constrained joint iterative optimization of filters according to the minimum variance criterion. The proposed optimization procedure adjusts the parameters of a projection matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. We describe LCMV expressions for the design of the projection matrix and the reduced-rank filter. We then describe stochastic gradient and develop recursive least-squares adaptive algorithms for their efficient implementation along with automatic rank selection techniques. An analysis of the stability and the convergence properties of the proposed algorithms is presented and semi-analytical expressions are derived for predicting their mean squared error (MSE) performance. Simulations for a beamforming application show that the proposed scheme and algorithms outperform in convergence and tracking the existing full-rank and reduced-rank algorithms while requiring comparable complexity.     

Wavelet footprints: theory, algorithms, and applications

Wavelet-based algorithms have been successful in different signal processing tasks. The wavelet transform is a powerful tool because it manages to represent both transient and stationary behaviors of a signal with few transform coefficients. Discontinuities often carry relevant signal information, and therefore, they represent a critical part to analyze. We study the dependency across scales of the wavelet coefficients generated by discontinuities. We start by showing that any piecewise smooth signal can be expressed as a sum of a piecewise polynomial signal and a uniformly smooth residual (Theorem 1). We then introduce the notion of footprints, which are scale space vectors that model discontinuities in piecewise polynomial signals exactly. We show that footprints form an overcomplete dictionary and develop efficient and robust algorithms to find the exact representation of a piecewise polynomial function in terms of footprints. This also leads to efficient approximation of piecewise smooth functions. Finally, we focus on applications and show that algorithms based on footprints outperform standard wavelet methods in different applications such as denoising, compression, and (nonblind) deconvolution. In the case of compression, we also prove that at high rates, footprint-based algorithms attain optimal performance (Theorem 3).     

Maximum likelihood estimation, analysis, and applications ofexponential polynomial signals

We model complex signals by approximating the phase and the logarithm of the time-varying amplitude of the signal as a finite order polynomial. We refer to a signal that has this form as an exponential polynomial signal (EPS). We derive an iterative maximum-likelihood (ML) estimation algorithm to estimate the unknown parameters of the EPS model. The initialization of the ML algorithm can be performed by using the result of a related paper. A statistical analysis of the ML algorithm is performed using a finite-order Taylor expansion of the mean squared error (MSE) of the estimate about the variance of the additive noise. This perturbation analysis gives a method of predicting the MSE of the estimate for any choice of the signal parameters. The MSE from the perturbation analysis is compared with the MSE from a Monte Carlo simulation and the Cramer-Rao Bound (CRB). The CRB for this model is also derived     

光电子显微术的原理和应用

近十年来,光电子显微技术取得了长足进步并已商业化。光电子显微是一种高衬度的成像技术,对材料表面电子结构高度敏感。本文介绍光电子显微镜的成像原理,并着重分析其衬度机制。简要总结光电子显微术在表面结构分析,表面化学,磁学,以及半导体器件表征等方面的应用。目前光电子显微术的两个重要发展方向是利用同步辐射光源和脉冲激光光源做激发源;利用脉冲激光的多光子激发光电子显微术可以对较高功函数（大于光子能量）的材料成像;而脉冲时间分辨光电子显微术可用来研究表面瞬态电子的弛豫动力学机制。文章介绍了在实现飞秒时间分辨以及多光子激发的光电子显微方面的进展。我们利用多光子光电显微术对溅射制备的纳米结构银薄膜表面进行成像,结果表明多光子成像照片上存在一些高强度的亮点,而在单光子成像照片未观察到类似现象。推测这些亮点源于纳米结构银表面的等离子激元的高局域选择性激发。文章还介绍了利用光电子显微术原位观察CuZnAl形状记忆合金的热诱导相变。     

Interference estimation and its applications in cognitive radio networks

Cognitive Radio (CR) has been proposed as a system-level means to improve the spectrum utilization efficiency. The most significant premise for CR networks is to avoid harmful interference to the licensed users. Therefore, it is very important to estimate the potential interference introduced by the deployment of CR networks so that CR networks can be coexistence with Licensed User (LU) networks by designing proper system parameters. In this paper, two statistical models of potential interference due to CR networks are developed based on transmitter and receiver oriented spectrum sensing schemes, respectively. The approximate probability distributions of aggregate interference introduced by CR networks are then derived with respect to the obtained models. With the help of these probability distributions, a method is further presented to get the critical system parameter, i.e., sensing distance and user density of the CR networks, so that the introduced interference can be controlled to predefined level. Numerical results validate the proposed interference estimation method and confirm the effectiveness of interference distribution based system parameter design.     

DVB-T中非自适应和自适应信道估计算法的实现

信道估计的精确性对整个DVB-T接收系统的性能提高至关重要.在现有信道估计的算法中,线性估计和多项式估计不适用于环境恶劣的信道;FFT和IFFT估计实现代价太大;盲反卷积估计需要预先知道信道的统计参数,而信道统计参数的获得需要额外的代价;经典Wiener估计不仅需要获得信道的统计参数,而且需要对矩阵进行求逆,这就大大增加了算法的计算量.本文提出了两种信道估计的算法--二维FIR信道估计和二维自适应Wiener信道估计,这两种方法不需要预先知道信道的统计参数信息,不仅减少了运算复杂性,而且在实际中具有很好的性能.