The basic principle of variable step - size algorithm is analysed , as the facter of variable step - size algorithm mse , the non - linear function of error signal , autocorrelation of error signal and the kurtosis of error signal is proposed , and four new variable step - size cma is achieved . 3 . the kurtosis of equalizer output as a new variable step - size facter is propose , which provide an alternative method of variable step - size , and a new variable step - size cma by putting it into cma is achieved 3 、分析了将输出信号的峰度用于步长控制的可行性，为变步长算法步长的控制参量提供了新的选择，并将其应用于恒模算法的步长控制，得到一种新的恒模改进算法，并通过计算机仿真实验验证了改进算法优良的收敛性能。
The initialization method to achieve different equalizer delay local minimum is proposed for btea and se . comparison study using several uwac with different zero locations is made to demonstrate the equivalent of different initialization method for least mean square ( lms ) algorithm , btea , se and cma 尽管常数模盲均衡算法的初始化仍然是一个公认的未能解决的问题，但本文通过几条不同零点位置的水声信道，对比研究了自适应最小均方误差算法、倒三谱算法、超指数算法和常数模算法的不同权向量初始化的等效性。
Utilizing the idea of sfs ( shape from shading ) and the facial constrained information , we reconstruct face model by single frontal face image . we utilize orthogonal image method to generate individualized face model by adjusting the parameters of the candide - 4 . we realize an algorithm based on minimum features for rapid face modeling from video , by tracking feature points , calibrating exterior parameter , estimating 3d location of feature points 利用shapefromshading的思想和人脸的约束信息实现了基于单幅正面人脸图像的重建；以candide - 4的参数调整为手段实现基于两幅正交图像的人脸模型重建；通过跟踪视频中的特征点，标定相机外参，进而估计特征点的3d位置，实现了基于一段视频中小特征点集的人脸建模算法。
Therefore , the blind beamforming algorithm could keep up with the moving targets more quickly , which is important in practical communication systems . furthermore , the recursive cma to fast track several cm targets is provided . the simulation results show that it takes about one seventh of the time for the recursive algorithm to track the targets than that of the traditional algorithm 针对多个恒模用户信号，具体给出了快速跟踪移动目标的递归恒模算法，计算机仿真结果表明，使用新算法跟踪移动目标所花费的时间是传统算法独立地进行每一次波束形成所花费时间的七分之一。
The constant modulus algorithm ( cma ) is the most widely used algorithm in digital communication systems due to its simplicity and robustness . in this paper we analysis the inherent limitation of cma which lead to a tradeoff between convergence rate and misadjustment , and propose several variable step size cma by putting variable step - size theories into cma . the convergence performance of the proposed algorithms is illustrated by computer simulations 本文对数字通信系统中广泛应用的bussgang类盲均衡算法? ?恒模算法( cma )进行了深入研究，分析了制约其性能进一步提高的因素，将变步长理论应用于恒模算法，提出了一系列恒模改进算法，并通过计算机仿真对改进算法的收敛性能进行了验证。
The definitions of fuzzy colored petri net and fuzzy petri net are modified . and two modeling algorithms based them are proposed to solve issues of existing fuzzy petri net models . therefore , fuzzy petri net models can reason correctly complex problems according to mechanism in themselves 扩展了模糊有色petri网系统和模糊petri网系统，并分别提出了两者的推理建模算法，以解决己有模糊petri网模型存在的问题，使模糊petri网能够完全依靠自身机理实现复杂实际问题的正确推理。
After the ls - cma captures a cm signal , the relationship between the weight vector and the do a of the other signals is derived . initial weight vectors are set hi the directions of the other cm signals by lcmv algorithm . thereafter , the blind beamforming for the other cm signals can also be realized 首先，我们导出了恒模算法收敛于任意一个恒模信号后，其恒模算法的权向量与其它用户波达角之间的关系，然后在不同用户的波达方向上形成初始增益，进而对所有的用户实现波束形成。
This thesis first describes the general research development of bp network , kde , genetic algorithm , arx model and their specific application in dms such as architecture , algorithm - flow etc . then the paper introduces the distributed object technique with the focus on the description of corba and the specific developing tools visibroker . finally , a multi - client distributed monitoring system based on corba is developed with multi - technologies referred before 本文首先系统地介绍了bp神经网络、核函数概率估计( kde ) 、遗传算法( ga )和带外生变量的自回归模型( arx )发展和研究概况以及上述建模算法在分布式监测系统中的应用,并给出了运用石油流化催化裂化模拟设备的数据测试结果。
2 to overcome the shortcoming of the interference capture caused by the least square cma ( ls - cma ) under severe environment , we provide the preprocessing ls - cma which combine the advantage of the stochastic gradient descent cma and the ls - cma . the simulation results confirm its effectiveness and feasibility . with the preprocessing controlled by the stochastic gradient descent cma , the ls - cma rejects the interference capture and converges to the user signal with weak power 2针对最小二乘恒模算法在强干扰环境下产生干扰捕获的缺点，结合随机梯度恒模算法和最小二乘恒模算法的特点，提出了预处理最小二乘恒模算法，计算机仿真结果证明，经过随机梯度恒模算法控制的预处理过程，最小二乘恒模算法克服了干扰捕获的缺点，收敛于弱功率用户信号，并取得了较好的信干噪比。
A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand . deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time , the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm . moreover , by introducing memory function and vaccine inoculation mechanism of immune system , at the same time , deca can converge to the optimal solution rapidly and stably . the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models . the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples , and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes 针对模糊聚类算法不适应复杂环境的问题,提出了一种新的动态进化聚类算法,克服了传统模糊聚类建模算法须事先确定规则数的缺陷.通过改进的遗传策略来优化染色体长度,实现对聚类个数进行全局寻优;利用fcm算法加快聚类中心参数的收敛;并引入免疫系统的记忆功能和疫苗接种机理,使算法能快速稳定地收敛到最优解.利用这种高效的动态聚类算法辨识模糊模型,可同时得到合适的模糊规则数和准确的前提参数,将其应用于控制过程可获得高精度的非线性模糊模型
