含软判决引导的修正恒模盲均衡算法

在CMA算法基础上，提出了一种混合的修正恒模盲均衡算法MCMA＋SDD。新算法对CMA算法进行修正，同时引入软判决思想。理论分析和计算机模拟表明，该算法克服了CMA收敛速度慢、稳态误差大的缺点，同时可以纠正相位偏转。与CMA＋SDD算法相比，具有更快的收敛速度和更低的稳态均方误差。     

判决引导和常数模融合盲均衡算法研究

结合判决引导（DD：Decision-Directed）算法和常数模算法（CMA：Constant Modulus Algorithm）的各自优点,研究了一种基于DD和CMA的融合盲均衡算法。DD算法收敛速度快,但要求初始接收信号眼图张开,CMA算法稳健,但是收敛速度慢,为此,对接收信号依DD算法和CMA算法获得瞬时误差后进行加权融合处理,以加权后获得的瞬时误差对均衡器权系数进行调节,实现均衡。计算机仿真证明了融合盲均衡算法有效提高收敛速度的同时具有良好的稳健性和均衡性能。     

盲信道均衡的动量恒模算法

介绍了盲信道均衡恒模算法（CMA）的基本原理，对恒模算法的缺点进行了分析，通过修正恒模算法的迭代公式提出一种动量恒模算法（MCMA）。利用QPSK信号，采用计算机仿真的方法对动量恒模算法与恒模算法进行盲均衡性能比较，模拟结果显示，MCMA算法比CMA算法在收敛速率、降低稳态均方误差和符号间干扰具有明显的优势，有效地改进了信道均衡性能。     

线性修正下的神经网络盲均衡算法

研究了一种利用横向滤波器对神经网络进行线性修正的盲均衡算法。在神经网络的输入层之前加入一个横向滤波器,以横向滤波器的节点输出作为神经网络盲均衡器的输入,利用常数模代价函数分别得到横向滤波器和神经网络盲均衡器的瞬时输出误差,将瞬时误差加权处理作为调节误差分别对横向滤波器和神经网络盲均衡器的权系数进行调节,算法实现了对非凸性误差曲面进行线性和非线性寻优的组合。计算机仿真证明提出的算法有效提高了神经网络盲均衡算法的收敛速度,降低了稳态剩余误差,具有更好的实用性和均衡性能。     

基于误差信号的双模式遗传盲均衡算法研究

DD算法具有收敛速度快,稳态剩余误差小的优点,是一种最常用的盲均衡算法。遗传盲均衡算法是一种新的盲均衡算法,它利用遗传算法来解决盲均衡问题,具有较好的全局优化特性。在综合研究了DD算法及遗传盲均衡算法的特性后,利用误差信号的特性,给出了一种新的双模式遗传盲均衡算法,有效的结合了DD算法以及遗传盲均衡算法的优点,大大提高了算法的运算速度,提升了收敛性能,解决了遗传盲均衡算法运算量大的问题,并通过计算机仿真验证了该算法的有效性。     

适用于无线传感器节点的低复杂度CCVSLMS均衡器研究

针对无线传感器节点的均衡算法--最小均方误差(LMS)算法和截断数据LMS算法或截断误差LMS算法(CLMS算法)的收敛速度、稳态误差性能的不足,进行了截断误差和截断数据可变的步长LMS算法(CCVSLMS算法)的研究,该算法通过对误差和数据进行截断处理和建立步长因子μ与截断变化率的线性函数关系来改善收敛速度和稳态误差...     

变步长LMS自适应均衡算法研究

为解决宽带无线通信中由多径信道产生的符号间干扰,对最小均方(LeastMeanSquares,以下简称LMS)自适应均衡算法进行深入分析。针对LMS算法收敛速度和稳态均方误差相互矛盾的问题,重点研究变步长LMS算法,在现有算法的基础上,进行步长分析,提出一种新型变步长LMS算法。利用信道响应长度、均衡器阶数、收敛误差共同控制迭代步长,简化步长设置,提升算法的收敛速度并降低稳态均方误差。仿真分析表明新型变步长LMS算法有更好的收敛特性。     

适用于水声信道的新的盲均衡算法

由于时变水声信道的随机相位失真，常模算法（CMA）的误码性能将严重下降。在文献[1]中双模式盲均衡算法的基础上，提出了一种适用于水声信道的新的盲均衡算法（NCMA）。计算机仿真结果表明在时变水声信道中，该算法性能优于双模式算法，能够达到信号相位失真的恢复．并且收敛性能优于双模式算法。     

减少自适应均衡算法计算量的研究

通信系统中广泛地使用基于LMS算法的自适应均衡器,常数模(CMA)盲均衡算法也开始在实际中使用。在高速通信中,算法迭代中的大量乘法运算会产生延迟,因此需要尽量减少。符号误差LMS及常数模盲均衡算法虽计算量小,但性能较原算法有较大下降。本文采用以2的整数次幂对LMS及CMA算法的误差项进行了量化,并将该方法应用到与之对应的判决反馈结构之中。该种量化方法不仅使权向量迭代中的乘法大大简化,且由于量化的比特数较多,性能比2bits量化的符号类算法还有很大改进。计算机仿真证明了该误差量化方法的有效性。     

基于正方形星座图划分的水声信道盲均衡算法

本文提出了一种适用于高阶QAM信号的盲均衡算法，该算法分别对QAM信号的同相分量和正交分量进行均衡，其收敛后的性能优于常数模算法CMA和基于判决圆划分的算法，因而误码率较低．采用分数间隔系统进行水声多途信道的仿真实验验证了该算法良好的收敛性能．     

一种新的用于3G互连的盲均衡改进算法TDE—CMA

DVB中广泛使用的CMA均衡算法一直深受伪收敛问题的困扰。从CMA算法的代价函数、迭代方程 及初始化系数等方面对伪收敛问题进行研究,在此基础上提出一种带时延估计的CMA改进算法。该算法通过引 入时延校正因子来调整主径的位置,从而避免了伪收敛现象。计算机仿真表明该方法大大提高了原算法的收敛 性,并且具有运算量小、易实现的优点,是一种实用性较强的改进算法,适用于高速的３G互连应用。     

Fiber Raman gain amplifier performance study using simple coupled-mode analysis

The propagation characteristics of doped fiber amplifier have, already, been analyzed using simple coupled-mode analysis (CMA), which steers the interests to apply this simple theory to study the amplification performance of fiber Raman gain amplifier (FRGA). But such study is yet to be done for FRGA. In this paper, a premier report based on CMA is presented to analyze and predict the performance of FRGA for first time, as per our knowledge, using coaxial structure consisting of step-index profiles in both inner and outer cores in terms of effective area, Raman gain coefficient, and effective Raman gain coefficient. In our investigation, we use single pump to compute and compare our results with the results obtained by involved matrix method and a fairly excellent match over a wide region of frequency shift is reported.     

Hardware-assisted initialisation for constant modulus algorithm adaptive antenna

A cost-effective approach for initialisation of an adaptive antenna based on the constant modulus algorithm (CMA) is proposed. The technique utilises 1 bit phase shifters and a power detector, which are normally integrated with a multibeam antenna, to determine the maximum power beam direction. Consequently, the beam is exploited as an initial beam for CMA. Development of hardware-assisted initialisation is discussed. In addition, field programmable gate array implementation of a CMA processor and associated control circuitry is presented. Several simulations are performed to evaluate the performance of the proposed initialisation technique. In addition, the developed prototype is tested with a phase array antenna designed for operation at the IMT2000 frequency of 1.95 GHz. Experimental results confirm superiority of the proposed technique.     

Space-time constant modulus algorithm for multipath removal on the reference signal exploited by passive bistatic radar

The authors address the problem of multipath cancellation in the reference signal used in passive bistatic radar (PBR), which exploits an existing transmitter as emitter of opportunity. The presence of multipath echoes in the reference signal is demonstrated to strongly affect the detection performance of passive radar. Based on the well-known constant modulus algorithm (CMA) approach in the time-domain, new multi-dimensional techniques are considered for the adaptive equalisation of the reference signal based on an array of antennas and multiple receiving channels. The effectiveness of these techniques for PBR purposes is demonstrated with reference to typical simulated scenarios. The considered strategies, addressed as space-CMA and space-time-CMA, are shown to be able to recover the performance loss because of the multipath contribution in the reference signal so that they appear as very appealing solutions for PBR equipped with an array of antennas and multiple receiving channels.     

A competitive memetic algorithm for the distributed two-stage assembly flow-shop scheduling problem

This article addresses the distributed two-stage assembly flow-shop scheduling problem (DTSAFSP) with makespan minimisation criterion. A mixed integer linear programming model is presented, and a competitive memetic algorithm (CMA) is proposed. When designing the CMA, a simple encoding scheme is proposed to represent the factory assignment and the job processing sequence; and a ring-based neighbourhood structure is designed for competition and information sharing. Moreover, some knowledge-based local search operators are developed to enhance the exploitation ability. The influence of parameter setting on the CMA is investigated using the analysis of variance method. Extensive computational tests and comparisons are carried out, which demonstrate the effectiveness of the proposed CMA in solving the DTSAFSP.     

Fast converging approach for blind constant modulus interference suppression

Abstract

The convergence behavior of the constant modulus algorithm (CMA) is examined in the proper initialization condition of locking onto the desired signal. An improved CMA converging approach is proposed that has the advantage of suppressing multiple access interference without explicit knowledge of interference parameters for synchronous DS‐CDMA systems. Simulation results demonstrate that the method overcomes the slower convergence of the CMA in the sudden birth of the number of users and outperforms the CMA detector and matched filter.     

盲均衡算法的发展及其共性思考

引用大量科技文献，阐述了盲均衡算法的发展。从算法的角度，着重介绍了常量模板算法，基于高阶谱的算法，基于神经网络的算法等算法的发展情况，并对其优缺点进行了比较。同时，对各种算法的共性进行了探讨。     

Unequal-area stochastic facility layout problems: solutions using improved covariance matrix adaptation evolution strategy,particle swarm optimisation,and genetic algorithm

Determining the locations of departments or machines in a shop floor is classified as a facility layout problem. This article studies unequal-area stochastic facility layout problems where the shapes of departments are fixed during the iteration of an algorithm and the product demands are stochastic with a known variance and expected value. These problems are non-deterministic polynomial-time hard and very complex, thus meta-heuristic algorithms and evolution strategies are needed to solve them. In this paper, an improved covariance matrix adaptation evolution strategy (CMA ES) was developed and its results were compared with those of two improved meta-heuristic algorithms (i.e. improved particle swarm optimisation [PSO] and genetic algorithm [GA]). In the three proposed algorithms, the swapping method and two local search techniques which altered the positions of departments were used to avoid local optima and to improve the quality of solutions for the problems. A real case and two problem instances were introduced to test the proposed algorithms. The results showed that the proposed CMA ES has found better layouts in contrast to the proposed PSO and GA.     

Computational intelligence modelling of pharmaceutical tabletting processes using bio-inspired optimization algorithms

In pharmaceutical development, it is very useful to exploit the knowledge of the causal relationship between product quality and critical material attributes (CMA) in developing new formulations and products, and optimizing manufacturing processes. With the big data captured in the pharmaceutical industry, computational intelligence (CI) models could potentially be used to identify critical quality attributes (CQA), CMA and critical process parameters (CPP). The objective of this study was to develop computational intelligence models for pharmaceutical tabletting processes, for which bio-inspired feature selection algorithms were developed and implemented for optimisation while artificial neural network (ANN) was employed to predict the tablet characteristics such as porosity and tensile strength. Various pharmaceutical excipients (MCC PH 101, MCC PH 102, MCC DG, Mannitol Pearlitol 200SD, Lactose, and binary mixtures) were considered. Granules were also produced with dry granulation using roll compaction. The feed powders and granules were then compressed at various compression pressures to produce tablets with different porosities, and the corresponding tensile strengths were measured. For the CI modelling, the efficiency of seven bio-inspired optimization algorithms were explored: grey wolf optimization (GWO), bat optimization (BAT), cuckoo search (CS), flower pollination algorithm (FPA), genetic algorithm (GA), particle swarm optimization (PSO), and social spider optimization (SSO). Two-thirds of the experimental dataset was randomly chosen as the training set, and the remaining was used to validate the model prediction. The model efficiency was evaluated in terms of the average reduction (representing the fraction of selected input variables) and the mean square error (MSE). It was found that the CI models can well predict the tablet characteristics (i.e. porosity and tensile strength). It was also shown that the GWO algorithm was the most accurate in predicting porosity. While the most accurate prediction for the tensile strength was achieved using the SSO algorithm. In terms of the average reduction, the GA algorithm resulted in the highest reduction of inputs (i.e. 60%) for predicting both the porosity and the tensile strength.