Convergence and performance analysis of the normalized LMSalgorithm with uncorrelated Gaussian data

It is demonstrated that the normalized least mean square (NLMS) algorithm can be viewed as a modification of the widely used LMS algorithm. The NLMS is shown to have an important advantage over the LMS, which is that its convergence is independent of environmental changes. In addition, the authors present a comprehensive study of the first and second-order behavior in the NLMS algorithm. They show that the NLMS algorithm exhibits significant improvement over the LMS algorithm in convergence rate, while its steady-state performance is considerably worse     

Comments on `On the use of the Hilbert transform for processingmeasured CW data'

The commenters relate the work of F.M. Tesche (see IEEE Trans. Electromag. Compatibility, vol.34, no.3, pp.259-266, 1992), in which he invokes causality to recover a transient-time response from magnitude-only spectral data using minimum-phase reconstruction and proposes a Hilbert filter as a means of correcting complex-valued spectral data that have been corrupted by noise, again invoking causality in the resulting processed noise contribution to their previous research on this topic (see Proc. Inst. Elec. Eng., vol.137, pt.H, pp.184-188, June 1990)     

Uncertain data analysis algorithm based on fast Gaussian transform

The effect of the uncertainties needs to be taken full advantage during uncertain data clustering.An uncertain data clustering algorithm based on fast Gaussian transform was proposed,to solve the problems about the impact on the accuracy of clustering results and the clustering efficiency caused by the uncertainties,during the construction of uncertain data models and the distance measurement,which existed in the current researches.First,the data model according to the characteristic of the uncertainty distribution was constructed,without the premise of assuming the data distribution.And the similarity between uncertain data objects was measured by combining the two important features of uncertain objects,attribute features and the probability density function representing the characteristic of uncertainty distribution.And then the uncertain data clustering algorithm was proposed.Finally,the experiment results on UCI and real datasets indicate the better efficiency and accuracy of proposed algorithm.     

基于SRLG不相关的共享通路保护算法

网络的生存性技术是WDM光网络中的关键技术之一.在共享风险链路组(SRLG)的约束下,综合考虑了备选路由集合和波长层次的策略,提出了一种共享通路保护算法,对该算法进行了仿真研究,并对仿真结果进行了分析.     

AMBE算法的特性分析与研究

首先简要介绍了MBE算法的原理以及目前常月的ACELP、VCELP等几种其他算法。在此基础上,介绍对各种算法的质量评价方法;之后从不同参数角度时几种语音编码算法进行分析比较,分析在AMBE算法一定环境下的优越性;最后给出AMBE算法下的语音压缩模块的测试结果。     

Leaky LMS algorithm: MSE analysis for Gaussian data

Despite the widespread usage of the leaky LMS algorithm, there has been no detailed study of its performance. This paper presents an analytical treatment of the mean-square error (MSE) performance for the leaky LMS adaptive algorithm for Gaussian input data. The common independence assumption regarding W(n) and X(n) is also used. Exact expressions that completely characterize the second moment of the coefficient vector and algorithm steady-state excess MSE are developed. Rigorous conditions for MSE convergence are also established. Analytical results are compared with simulation and are shown to agree well     

Quadratic forms in complex Gaussian matrices and performance analysis of MIMO systems with cochannel interference

This paper establishes an analytical framework for the performance analysis of multiple-input/multiple output (MIMO) systems subject to cochannel interference and operating over fading channels. First, we present some new statistical results dealing with the distribution of the largest eigenvalue of certain quadratic forms in complex Gaussian matrices and establish the connection between these results and the performance analysis of MIMO systems subject to cochannel interference. We consider interference limited systems in which the number of cochannel interferers exceeds or is equal to the number of receiving antenna elements. We then derive new "closed-form" expressions of the probability density function of the outage signal-to-interference ratio and the system outage probability for MIMO systems in Rician-Rayleigh (i.e., the desired user is subject to Rician fading while cochannel interferers are subject to Rayleigh fading) and Rayleigh-Rayleigh fading environments. When applicable, these expressions are compared to special cases previously reported in the literature dealing with the performance of single-input/multiple-output (SIMO) systems. As a double check, these analytical results and assumptions are validated by Monte Carlo simulations and as an illustration of the mathematical formalism some numerical examples for particular cases of interests are plotted and discussed. These results show that under the same the scattering and interfering conditions and given a fixed number of total antenna elements and cochannel interferers: 1) SIMO systems will always outperform multiple-input/single-output systems and 2) it is preferable to distribute the number of antenna elements evenly between the transmitter and the receiver for an optimum performance.     

Quadriphase DS-CDMA with pulse shaping and the accuracy of the Gaussian approximation for matched filter receiver performance analysis

Probability of bit-error (P/sub e/) performance of asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems is analyzed. In particular, the effects of pulse shaping, quadriphase (or direct-sequence quadriphase shift keying (DS-QPSK)) spreading, aperiodic spreading sequences and the coherent correlator or, equivalently, the matched filter (MF) receiver are considered. An exact P/sub e/ expression and several approximations: one using the characteristic function (CF) method, a simplified expression for the improved Gaussian approximation (IGA) and the simplified improved Gaussian approximation (SIGA) are derived. Two main results are presented. Under conditions typically satisfied in practice and even with a small number of interferers, the standard Gaussian approximation (SGA) for the multiple-access interference component of the MF statistic and for MF P/sub e/ performance is shown to be accurate. Moreover, the IGA is shown to reduce to the SGA for pulses with zero excess bandwidth. Second, the P/sub e/ performance of quadriphase DS-CDMA is shown to be superior or equivalent to that of biphase DS-CDMA. Numerical examples with Monte Carlo simulation are presented to illustrate P/sub e/ performance for square-root raised-cosine (Sqrt-RC) pulses and spreading factors of moderate to large values.     

Comments on the accuracy of the `Ludwig' integration algorithm

The accuracy of the so-called Ludwig algorithm for solution of integrals arising from electromagnetic radiation problems, first reported by the author in 1968 (ibid., vol.AP-16, p.767-9, Nov. 1968), is shown to be better than results reported by others for the case of the pattern of a uniformly illuminated aperture. It is argued that the accuracy is very similar to results obtained using a Romberg-Simpson technique, and computer speed is superior if more than 4-5 sidelobes are computed. A comparison is also made with very recent results, and it is shown that the Ludwig algorithm's accuracy is very competitive with the best results obtained with alternative techniques. The Ludwig algorithm does not exhibit the catastrophic failure shown by the alternative techniques and has the advantage of accepting data at arbitrary spacings     

LDPC码译码算法及性能分析

为了进一步降低低密度奇偶校验(LDPC)码译码算法的复杂度,基于经典置信传播(BP)译码算法,给出了对数域迭代后验概率对数似然比(APP LLR)算法。通过概率域的和积算法(SPA)和对数域的迭代APP LLR算法的性能仿真及分析可见,迭代APP LLR算法能以较小的性能损失换取复杂度的大幅降低。进一步选用迭代APP LLR算法,结合不同地形条件下的VHF频段信道模型,仿真了LDPC码编译码系统的性能。理论分析及仿真结果均表明,基于迭代APP LLR算法的LDPC码,实现简单,性能优异,具有良好的工程应用前景。     

Stochastic analysis of the least mean fourth algorithm for non-stationary white Gaussian inputs

This paper studies the stochastic behavior of the least mean fourth (LMF) algorithm for a system identification framework when the input signal is a non-stationary white Gaussian process. The unknown system is modeled by the standard random-walk model. A theory is developed which is based upon the instantaneous average power and the instantaneous average squared power in the adaptive filter taps. A recursion is derived for the instantaneous mean square deviation of the LMF algorithm. This recursion yields interesting results about the transient and steady-state behaviors of the algorithm with time-varying input power. The theory is supported by Monte Carlo simulations for sinusoidal input power variations.     

Comments on the performance of maximum entropy algorithms

Two points recently brought up in this journal concerning the performance of maximum entropy spectral analysis are discussed. First, an additional recursive formula is presented which simplifies and reduces the computational load of the Burg algorithm. Second, attention is drawn to some recent results in the geophysics literature related to the proper selection of prediction filter length.     

Steady-state analysis of quantized distributed incremental LMS algorithm without Gaussian restriction

In this paper, we analyze the steady-state performance of the distributed incremental least mean-square (DILMS) algorithm when it is implemented in finite-precision arithmetic. Our analysis in this paper does not consider any distribution of input data. We first formulate the update equation for quantized DILMS algorithm, and then we use a spatial-temporal energy conservation argument to derive theoretical expressions that evaluate the steady-state performance of individual nodes in the network. We consider mean-square error, excess mean-square error, and mean-square deviation as the performance criteria. Simulation results are generated by using two types of signals, Gaussian and non-Gaussian distributed signals. As the simulation results show, there is a good match between the theory and simulation.     

基于NC-MUSIC算法的均匀圆阵DOA估计及性能分析

近年来基于非圆信号的DOA估计算法由于其优良的估计性能,受到越来越多的关注。在接收阵列为均匀圆阵的情况下,对入射信号进行方位角和俯仰角的联合估计。依据非圆信号的DOA估计数学模型及阵列模型,采用NC-MUSIC算法完成对均匀圆阵方位角和俯仰角的联合估计。通过计算机仿真,得出该算法对均匀圆阵方位角和俯仰角的估计是比较准确的,并且通过NC-MUSIC与MUSIC算法仿真性能的分析比较,得出在接收阵列为均匀圆阵的情况下,NC-MUSIC算法也优于MUSIC。     

Positioning performance analysis of the time sum of arrival algorithm with error features

The theoretical positioning accuracy of multilateration (MLAT) with the time difference of arrival (TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival (TSOA) algorithm from the root mean square error (RMSE) and geometric dilution of precision (GDOP) in additive white Gaussian noise (AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.     

Statistical performance analysis of the algebraic constant modulus algorithm

This paper presents a large sample analysis of the covariance of the beamformers computed by the analytical constant modulus algorithm (ACMA) method for blindly separating constant modulus sources. This can be used to predict the signal-to-interference plus noise ratio (SINR) performance of these beamformers, as well as their deviation from the (nonblind) Wiener receivers to which they asymptotically converge. The analysis is based on viewing ACMA as a subspace fitting optimization, where the subspace is spanned by the eigenvectors of a fourth-order covariance matrix. The theoretical performance is illustrated by numerical simulations and shows a good match.     

自适应扩散算法的误差性能分析

为了分析分布式协作频谱感知认知网络中融合矩阵、步长等参数对自适应扩散算法的影响,对检测量估计误差性能进行了研究。给出了自适应扩散算法检测量的通用迭代公式,分析了检测算法的数据处理流程;推导了检测量估计误差向量的迭代表达式,利用网络瞬时均方偏差性能和各节点的稳态均方偏差性能评价融合矩阵参数对算法的影响。结果表明,不同的融合矩阵选取原则影响算法的检测性能,可以采用检测量误差估计的方法对算法参数进行研究。     

裁减自动球形译码算法与性能分析

提出了裁减自动球形译码（PASD）算法。该算法利用统计裁减有效减小了自动球形译码（ASD）算法中边界节点列表的大小S，并可通过对参数的适当设置获得误符号率性能与复杂度之间的折衷。分析与仿真表明，当采用较高电平调制（电平数大于4）时，在相同信噪比范围内，PASD在几乎不损失误符号率性能的前提下，较ASD节省大于30％的比较次数。     

多业务量矩阵下流量工程算法性能研究

传统域内流量工程TE(traffic engineering)算法中,基于OSPF/IS-IS的TE思想是通过调整链路权重使得全网的负载最均衡.由于Internet的急速发展以及用户业务需求的动态性导致业务量矩阵的不确定性,多业务量下的TE算法研究显得很有必要,而对于多业务量矩阵采取这种算法来最优化网络的研究很少见.本文提出了一种新的启发式基于OSPF/IS-IS链路权重调整的TE算法来解决多业务量矩阵,通过大量仿真实验分析了影响该算法性能的因子,从而为网络规划提供了很好的参考价值.