m相依噪声情况下随机信号的Robust—M检测

本文就随机信号情形对ｍ相依噪声进行检测，给出了最不利密度函数及最佳的Ｒｏｂｕｓｔ－Ｍ检测器，仿真例子表明它能很好的检测随机信号。     

m相依噪声情况下随机信号的Robust－M检测

本文就随机信号情形对ｍ相依噪声进行检测，给出了最不利密度函数及最佳的Ｒｏｂｕｓｔ－Ｍ检测器，仿真例子表明它能很好地检测随机信号．     

污染型类高斯噪声中信号的Robust-SA检测

采用了Ｒｏｂｂｉｎｓ－Ｍｏｒｒｏ随机逼近算法，得到了Ｒｏｂｕｓｔ－ＳＡ检测器。它的主要特点是具有Ｍ－检测器的优点，且便于实时处理和计算机编程。理论分析与仿真例子都表明：此检测器具有良好的顽健性，能很好的检测信号。     

基于谱减的Robust电话语音识别方法

谱减技术是语音增强的有效方法，并被成功地应用到了车辆等环境下的Ｒｏｂｕｓｔ语音识别中。文章对将谱减技术应用到电话语音识别中的加性噪声去除上进行了尝试。实验验证该方法有利于改进电话语音识别的性能，对不特定话音８４个孤立词的实验，误识率下降了２１．８％。     

一种便于观测的信号抽样及复原方法

利用倍频器，将重复频率与连续信号ｔ（ｔ）的频率相同的方波进行若干次倍频后，对连续信号进行抽样，从而获得离散的抽样信号ｆｓ（ｔ），再利用有源低通滤波器使其复原成连续信号ｆ（ｔ）。避免了一般抽样器不便于观测的缺点。     

螺量域波达方向估计的稳健性

本文提出了一种用于等矩线阵的四阶累重量域波达方向（ＤＯＡ）估计算法，并着重研究了算法的稳健性（Ｒｏｂｕｓｔｎｅｓｓ）该算法利用了空间累量阵中的所有非冗余量元素，并将相位相同不量元素做平滑处理。Ｔｏｅｐｌｉｔｚ化后形成新的虚拟协方差矩阵，方向估计基于此阵，分析表明，该算法对阵列误差有较强的容差性，加之累量对高斯噪声的自然盲性，因而算法具有稳健性，该算法的另一个特点是可以提供虚拟扩展孔径（扩展近两倍）     

形态谱的一般性构造形式及其鲁棒性分析

本文建立了形态谱一般性的构造形式，针对一噪声模型，分析了各种形态谱的鲁棒性（Ｒｏｂｕｓｔｎｅｓｓ），理论分析与实验计算表明通常形态谱的鲁棒性具有一定局限性。而高阶形态谱具有很好抗噪声侵蚀能力     

tss与MD110联网调试中话路“吊死”问题的分析处理

本文以ｔｓｓ和ＭＤ１１０联网调试中主波叫通话状态下同时挂机时话路出现“吊死”９０ｓ的现象为中心，分析了信令配合过程及产生问题的原因，介绍了解决的办法，提出了两点建议。     

一种基于交替序列形态变换的Robust形状描述方法

为了解决形状描述的Ｒｏｂｕｓｔｎｅｓｓ问题，本文提出了一种高阶形态谱，与通常形态谱不同的是，高阶谱与两个具有不同尺寸因子的交替序列形态变换（ａｌｔｅｒｎａｔｉｎｇｓｅｑｕｅｎｔｉａｌｍｏｒｐｈｏｌｏｇｉｃａｌｔｒａｎｓｆｏｒｍａｔｉｏｎ）结果相关，文中证明了在一定条件下，高阶谱的高阶因子与噪声的存在是无关的，计算结果亦已很好地证明了这一点。     

The Fast Blind Equalization Algorithm with Global Convergence

ＴｈｅＦａｓｔＢｌｉｎｄＥｑｕａｌｉｚａｔｉｏｎＡｌｇｏｒｉｔｈｍｗｉｔｈＧｌｏｂａｌＣｏｎｖｅｒｇｅｎｃｅＬｕＪｕｎＬｉＴｏｎｇ（ＩｎｓｔｉｔｕｔｅｏｆＩｎｆｏｒｍａｔｉｏｎａｎｄＥｎｇｉｎｅｅｒｉｎｇｏｆＰＬＡ，Ｚｈｅｎｇｚｈｏｕ４５０００２）Ａ...     

基于FM0记忆辅助特性的RFID标签碰撞检测

为实现两个射频识别(RFID)碰撞标签信息的检测和分离，提出一种利用Gen2标准中FM0标签编码固有记忆特性的检测方法。通过对FM0比特编码特点和碰撞标签信息的无记忆检测分析，得到基于单个比特持续时间的无记忆检测方法的条件错误概率和单个标签信息检测的误码率；然后利用单个FM0比特编码需要前一比特的“记忆”特性，得到对应于前一比特的一对测量值和对应于下一比特的一对测量值，进而得到碰撞标签信息的1比特记忆辅助检测时的条件错误概率和误码率性能；并对在帧Aloha媒质接入方案中采用提出的检测方法时的N个标签群的总延迟减少性能进行了分析。仿真实验结果表明，提出的1比特记忆辅助检测方法，相比于无记忆检测具有更好的误码率性能，且能减少标签群接入时的总延迟。     

复合高斯杂波下基于GLRT的扩展目标检测

广义似然比检测(Generalized Likelihood Ratio Test,GLRT)是解决复合高斯杂波下扩展目标检测问题的一种有效方法,而当目标速度未知时,经典的GLRT失效。该文针对目标速度未知的情形,提出了一种基于广义特征值分解的扩展目标多普勒频率估计算法,可有效估计多普勒频率,并以此为基础设计了一种R-GLRT(Robust GLRT)检测器。仿真结果表明了这种检测器的有效性。     

Semantic loop closure detection based on graph matching in multi-objects scenes

Robust loop-closure detection is essential for visual SLAM. Traditional methods often focus on the geometric and visual features in most scenes but ignore the semantic information provided by objects. Based on this consideration, we present a strategy that models the visual scene as semantic sub-graph by only preserving the semantic and geometric information from object detection. To align two sub-graphs efficiently, we use a sparse Kuhn–Munkres algorithm to speed up the search for correspondence among nodes. The shape similarity and the Euclidean distance between objects in the 3-D space are leveraged unitedly to measure the image similarity through graph matching. Furthermore, the proposed approach has been analyzed and compared with the state-of-the-art algorithms at several datasets as well as two indoor real scenes, where the results indicate that our semantic graph-based representation without extracting visual features is feasible for loop-closure detection at potential and competitive precision.     

Memoryless quantizer- detectors for constant signals in m-dependent noise

The performance and design of data quantizers for use in memoryless discrete-time detection systems operating with dependent samples is considered. This problem is approached on a large-sample-size small-signal basis, andm-dependence is used to model the dependence structure among data samples. By considering the particular situation of detecting known constant signals in additive noise, previous results for memoryless detector analysis are applied to derive expressions for the evaluation of quantizer-detector performance for this situation. Design criteria are established for the optimum selection of quantizer parameters, and these are seen to be generalizations of earlier designs for the corresponding independent sampling case.     

Accurate computation of the performance of M-ary orthogonal signaling on a discrete memoryless channel

A formula for the error rate of maximum-likelihood detection of M-ary orthogonal signaling on a discrete memoryless channel is manipulated into a form that avoids numerical imprecision when it is used to calculate low error rates.     

Intersymbol Interference with Orthogonal Signaling

The occurrence of both inter- and intrasymbol interference in a communications system utilizing orthogonal signals and memoryless correlation detection is described, and a system model is presented. A relationship between a bound on peak interference and time-bandwidth product for several well known orthogonal signal sets is reported.     

Decorrelating detectors for quasi-synchronous CDMA

To date, two forms of spread spectrum code division multiple access (CDMA) have been considered in the literature. Either synchronous CDMA, where all users are both chip and bit synchronized relative to each other, or asynchronous CDMA, where all users are neither chip nor bit synchronized relative to each other. Between these two extremes lies quasi-synchronous CDMA (QS-CDMA) where users are not chip synchronized but are approximately bit synchronized. Quasi-synchronous CDMA arises in microcell systems where the combined propagation time and delay spread produces a variation in the round trip delay time limited to a few chips.Detection of QS-CDMA at the base station is considered. It is shown that memoryless detection can be achieved by appending blank chips to the user's spreading codes.Two decorrelating detectors are proposed and analyzed. The first uses a matched filter bank to produce a discrete time signal, and the second uses a single oversampling integrate-and-dump filter to produce a discrete time signal. For the first detector, each matched filter is synchronized to its respective user, and for the second detector, the integrate-and-dump filter is synchronized to the base station transmissions. The performance of the two detectors is shown to be approximately equal provided the integrate-and-dump filter is sampled at least two times the chip rate.     

Two-dimensional memoryless detection of a random signal inphi-mixing non-Gaussian noise (Corresp.)

The problem is considered of designing memoryless detection systems for detecting random signals in qb-mixing noise environments. Assuming that the bivariate densities of the noise can be expressed in an infinite series expansion, the nonlinearity is expressed as a series expansion and the coefficients are found that maximize the asymptotic relative efficiency.