A novel adaptive classification scheme for digital modulations in satellite communication

To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines （SVM） in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types （i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK） at SNRS ranging from 0dB to 25dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.     

Adaptively robust filtering with classified adaptive factors

The key problems in applying the adaptively robust filtering to navigation are to establish an equivalent weight matrix for the measurements and a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information to the state parameter estimates. In this paper, an adaptively robust filtering with classified adaptive factors was proposed, based on the principles of the adaptively robust filtering and bi-factor robust estimation for correlated observations. According to the constant velocity model of Kalman filtering, the state parameter vector was divided into two groups, namely position and velocity. The estimator of the adaptively robust filtering with classified adaptive factors was derived, and the calculation expressions of the classified adaptive factors were presented. Test results show that the adaptively robust filtering with classified adaptive factors is not only robust in controlling the measurement outliers and the kinematic state disturbing but also reasonable in balancing the contributions of the predicted position and velocity, respectively, and its filtering accuracy is superior to the adaptively robust filter with single adaptive factor based on the discrepancy of the predicted position or the predicted velocity.     

基于图像分类的自适应图像水印新算法

随着网络多媒体技术的不断发展,版权保护问题变得十分重要。数字水印是实现版权保护的一种非常有效的方法,已经成为目前学术界研究的热点。文中提出了一种新的DCT域自适应数字图像水印算法,它利用图像子块特征分类结果对水印嵌入强度进行自适应调节,从而在确保水印不可见性的同时有效地增强了水印的强度,算法还综合运用了Arnold置乱变换,进一步增强了水印的安全性。实验结果表明,该算法对一些常见的信号处理操作如JPEG压缩、加噪、滤波、剪切等有较强的鲁棒性。     

变时间延迟的分块递归最小二乘估计

时间延迟估计方法时常出现于目标方程和距离的检测问题中.通常时延估计问题的数学模型可描述为 x_1(t)=s(t)+n_1(t) (1) x_2(t)=αs(t-τ_1)+n_2(t) (2)此处n_2(t)和n_2(t)分别为两接收信号中的干扰噪声。一般假定s(t),n_1(t)和n_2(t)是联合平稳的,且互不相关。时间延迟估计的目标就是通过对观测信号x_1(t)和x_2(t)的分析处理估算(2)式中出现的因子τ_1。     

一种稳健的二维自适应波束形成算法

针对已存在的各种二维capon波束形成器稳健算法性能单一,只能对1种或2种影响波束形成算法性能的因素具有稳健性,缺乏对多种情况都具有稳健性的缺点,提出一种基于空间谱估计的二维稳健自适应波束形成方案.首先,提出一种新的二维解相关空间谱估计算法,该算法将二维角度估计问题用4个一维空间谱估代替,并采用修正的MUSIC算法实现解相干,然后利用得到的角度信息构造虚拟干扰,克服观察方向误差并展宽零陷.仿真结果表明:该算法结合了空间谱估计技术和自适应波束形成技术的优点,对期望信号导向矢量误差、干扰到达角失配及信号相关等都具有足够的稳健性.     

一类不确定仿射非线性系统的自适应变结构控制

研究非匹配不确定仿射非线性系统的输出跟踪问题．针对系统中的参数不确定性,基于李亚普诺夫稳定性理论提出了一种分段控制方案,当控制误差大于一定范围时,采用自适应变结构控制方案,使得闭环跟踪系统全局渐近稳定,参数估计值收敛,系统信号保持有界,控制误差减小到零域附近时,切断变结构控制,避免了颤振现象的出现．理论研究和仿真结果证实了理论结果的正确性和有效性．     

多级混合自适应控制器的设计

设计了一种多极混合自适应控制器,解决了高阶复杂被控对象在以往的自适应控制中出现的不稳定问题。增强了控制系统的鲁棒性。     

组合电力系统自适应稳定器PSS的设计

介绍了一种用于经输电线与无限大母线连接的同步发电机的组合电力系统自适应稳定器的设计方案。与传统的电力系统稳定器不同，它包括几个自适应稳定器，且这些稳定器同时又并联工作。稳定控制信号由各个单一的电力系统自适应稳定器的加权获得。同时也研究了加权系数的选择方法。最后给出系统的仿真研究，结果表明该稳定器与以往电力系统稳定器相比具有较强的鲁棒性。     

基于自适应算法的电力系统可靠性评估

针对电力系统可靠性评估中Monte Carlo方法存在的计算效率低下的问题,提出应用自适应算法对系统状态进行概率分析。该算法采用变分运算分析和区间拟合的方法,实现在最优密度函数下抽样,降低计算方差。应用该方法对IEEE-RTS标准系统的发电部分进行了可靠性评估,并与采用常规抽样方法和重要抽样方法的评估结果做了比较,表明该算法在保证计算精度的前提下分别减少了87%和68%的抽样次数,对大型电力系统可靠性评估具有实用价值。     

基于自适应卡尔曼滤波的时变结构参数估计

在许多情况下,对于非平稳或性能随时间发生变化的结构,要求对结构的参数进行实时的跟踪与识别,此时传统的递推算法．如卡尔曼滤波等方法就不再适用,而需要采用具有一定跟踪能力的自适应递推算法．本文对自适应卡尔曼滤波方法在时变结构参数估计中的应用进行了分析,并对其跟踪性能进行了探讨．     

一类自适应神经网络模型的Hopf分叉研究

运用动力系统分叉理论,研究了一类自适应神经网络模型平衡点的稳定性及Hopf分叉发生的参数条件．     

增元通道增益不一致情况下一种新的DOA快速估计算法

提出一种在阵元通道增益不一致情况下多个空间窄带信号波达方向(DOA)的快速估计算法。与传统DOA估计算法完全不同,该算法通过对阵列输出数据的快速傅立叶变换(FFT),建立了FFT频谱与波达方向角的关系;利用这一关系并通过对FFT谱峰的搜索,从而实现了对波达方向的快速估计。讨论接收阵列阵元通道增益不一致对算法的影响,计算机模拟实验验证了算法的可行性。     

Small unmanned helicopter's attitude controller by an on-line adaptive fuzzy control system

Since small unmanned helicopter flight attitude control process has strong time-varying characteristics and there are random disturbances, the conventional control methods with unchanged parameters are often unworkable. An on-line adaptive fuzzy control system (AFCS) was designed, in a way that does not depend on a process model of the plant or its approximation in the form of a Jacobian matrix. Neither is it necessary to know the desired response at each instant of time. AFCS implement a simultaneous on-line tuning of fuzzy rules and output scale of fuzzy control system. The two cascade controller design with an inner (attitude controller) and outer controller (navigation controller) of the small unmanned helicopter was proposed. At last, an attitude controller based on AFCS was implemented. The flight experiment showed that the proposed fuzzy logic controller provides quicker response, smaller overshoot, higher precision, robustness and adaptive ability. It satisfies the needs of autonomous flight.     

多尺度自适应加权形态边缘检测方法

针对常用的多尺度边缘检测方法因卷积运算造成模糊图像边缘，提出一种多尺度自适应加权形态边缘检测方法，利用大小不同的结构元素提取图像边缘特征，在大尺度下抑制噪声，可靠地识别边缘，在小尺度下定位，再由粗到细跟踪边缘，得到边缘的位置，再由各尺度结构元的抗噪性确定加权值的大小，然后加权处理得到最后的边缘结果，实验表明，用多尺度自适应加权形态边缘检测算法可得到较理想的图像边缘。     

一种快速多普勒频偏估值的新方法

提出了一种利用反馈型自适应谱线增强器的新型多普勒频偏估值器。计算机模拟证明，该估值器在话带内完成高精度频偏估值仅需要５０ｍｓ，滤波器阶数仅为３０。     

2019年空时自适应处理技术研究热点回眸

空时自适应处理可以联合空域和时域进行二维自适应滤波,是运动平台雷达系统中进行杂波抑制和目标检测的关键技术。近年来,空时自适应处理技术迅速发展,其应用领域也在不断扩大。概述了2019年空时自适应处理领域所取得的重要研究进展,展望了未来空时自适应处理技术的发展趋势。     

适应性安全的多主密钥KP-ABE方案

功能加密能很好地满足多对多的网络环境下的机密性需求,功能性函数提供了比传统公钥更灵活的密文存取能力.已有的功能加密系统均只支持单主密钥功能性函数,本文提出了功能加密子类KP-ABE(key-policy attribute-based encryption)上的多主密钥适应性安全模型,该模型具有更强的表达能力及更广义的特性.利用线性多秘密共享方案,设计了该安全模型下的一个加密方案,并采用对偶法在标准模型下证明方案是IND-CPA(indistinguishability against chosen-ciphertext attacks)安全的.该方案加密数据的存取策略更为灵活,用户可根据权限存取多种类型的密文;提出的构造方法可应用于功能加密的其他子类,且计算量与单主密钥方案相比不存在线性扩张,具有较高的效率.     

Small unmanned helicopter's attitude controller by an on-line adaptive fuzzy control system

Since small unmanned helicopter flight attitude control process has strong time-varying characteristics and there are random disturbances,the conventional control methods with unchanged parameters are often unworkable.An on-line adaptive fuzzy control system(AFCS)was designed,in a way that does not depend on a process model of the plant or its approximation in the form of a Jacobian matrix.Neither is it necessary to know the desired response at each instant of time.AFCS implement a simultaneous on-line tuni...     

一种新型的基于自适应局部二值模式的纹理分类算法

局部二值模式(LBP)在纹理特征提取时,易受光照、旋转、噪声等复杂条件的影响.本文定义一种新型自适应局部二值模式,通过考虑模式的均匀度和相似度,来实现纹理模式分类和特征值计算.结合差分运算,分别在差分二值矩阵和差分绝对值矩阵上计算自适应纹理特征,并将两部分特征值连接成一个空域增强的特征向量,采用最近邻分类器完成图像分类识别.实验结果表明,该算法在复杂条件下具有更好的识别效果.