海杂波FRFT域的分形特征分析及小目标检测方法

针对海杂波背景下海情对小目标检测的严重影响, 本文研究了实测海杂波在分数阶Fourier变换(FRFT)域的分形特征, 分别提出了单、高尺度下的分形检测方法. 由数学定义推得, FRFT 在不同阶数和尺度情况下, 不具有一致的自相似特性, 采用多重分形趋势波动分析法确定分形参数H(q), 分析了海杂波在不同海情、距离和极化条件下的分形特征. 在单尺度基础上结合FRFT的变阶优势, 提出了阶数自适应的小目标检测方法; 高尺度条件下, 比较了不同因素对海杂波FRFT域多重分形参数的影响. 结果表明:海杂波FRFT域可用变换阶数的方法检测到湮没在复杂海情中的小信号, 检测门限多数提高200%以上, 比采用时域信号提高26.3%. H(q) 在负高尺度上具有明显的多重分形特征差异, H(q)-q曲线满足反正切分布, 纯海杂波与含目标数据的拟合幅值比分别大于1.8(HH)和1.4(VV), 为海杂波背景小目标检测提供了判定依据.     

海杂波的分段分数布朗运动模型

主要研究了分段分数布朗运动(PFBM)模型在雷达海杂波分形建模中的应用.由于自然界和人造系统中研究对象不具有数学上完美的分形特性, 从而研究对象的分形特性无法在整个尺度区间上成立, 传统上, 海杂波的单一分形模型仅利用无标度区间内海杂波的自相似信息进行参数估计, 并没有考虑海杂波在无标度区间以外的尺度下所包含的信息.分段分数布朗运动从频域角度对海杂波频谱进行分段描述, 对应到时域即从粗略尺度和精细尺度两方面描述海杂波时间序列.结合海杂波产生的物理背景, 该模型可以为海杂波时间序列在粗略尺度和精细尺度下表现出的不同粗糙度提供机理性解释.在此基础上, 还研究了具有不同多普勒频率的运动目标对海杂波的影响, 结果表明运动目标对粗略尺度和精细尺度下海杂波的影响程度是不同的.     

关于B0→π－l+ν l衰变过程分支比的计算

通过构造适当的关联函数,计算B→π跃迁形状因子f⁺_Bπ(q²),f _{Bπ(q²)和标量形状因子f⁰(q²),从而就能研究轻子质量对B⁰→π}     

第Ⅵ类两态叠加多模叠加态光场的等阶N次方Y压缩特性研究

本文构造了由多模相干态|{Z_j}〉q与多模虚相干态|{iZ_j}〉q这两者的线性叠加所组成的第Ⅵ类两态叠加多模叠加态光场|Ψ₆⁽²⁾〉q.利用多模压缩态理论,研究了态|Ψ₆⁽²⁾〉q的广义非线性等阶N次方Y压缩特性.结果发现:1)在压缩阶数N＝2p且p＝2l(l＝1,2,3,…,…)的条件下,无论各模的初始相位φ_j(j＝1,2,3,…,q)、态间的初始相位差(θ_pq^(R)-θ_pq^(I))以及各单相干态光场的平均光子数之和 R_j²等如何变化,态|ψ₆⁽²⁾〉q总是恒处于偶数阶等阶N-Y最小测不准态.2)在压缩阶数N＝2p且p＝2l+1(l＝0,1,2,3,…,…)的条件下,当各模的初始相位φj、态间的初始相位差(θ_pq^(R)-θ_pq^(I))以及各单模相干态光场的平均光子数之和 R_j²等分别满足一定的量子化条件(或者在特定的区间内连续取值)时,态|ψ₆⁽²⁾〉q的第一及第二这两个正交分量总可分别呈现出周期性变化的偶数阶的等阶N次方Y压缩效应.     

三明治结构Tan(B3N3H6)n+1 团簇的磁性和量子输运性质

利用密度泛函理论和非平衡格林函数方法, 本文对小尺寸团簇Ta_n(B₃N₃H₆)_n+1 (n ≤ 4)的磁性和量子输运性质进行了系统的研究. 计算结果表明, 此类体系采用三明治结构作为其基态并且具有较高的稳定性. 体系的磁矩随团簇尺寸的增大而线性增大. 当把Ta_n(B₃N₃H₆)_n+1团簇耦合到Au电极上时, 形成的Au-Ta_n(B₃N₃H₆)_n+1-Au体系在有限偏压下展示出了较强的自旋过滤能力, 因而可以被看做是一类新型的低维自旋过滤器.     

态|ψ3(3)〉q广义电场分量的等幂次N次方H压缩

构造了由多模复共轭相干态|{iZ_j^*}〉_q、多模复共轭虚相干态|{iZ_j^*}〉_q(j=1,2,…q)和多模真空态|{0_j}〉_q线性叠加所组成的第Ⅲ类三态叠加多模叠加态光场|ψ₃⁽³⁾〉_q.利用多模压缩态理论,研究了态|ψ₃⁽³⁾〉_q中广义电场分量(即第二正交相位分量)的广义非线性等幂次N次方H压缩特性.发现:态|ψ₃⁽³⁾〉_q是一种典型的三态叠加多模非经典光场;当腔模总数q与压缩次数N之积q·N为偶数时,在一定条件下,态|ψ₃⁽³⁾〉_q的广义电场分量可分别呈现出周期性变化的广义非线性等幂次奇数模-偶数次、偶数模-奇数次、偶数模-偶数次N次方H压缩效应.     

多模叠加态光场|ψ5(3)〉q中广义磁场4m次方Y压缩

构造了由多模复共轭相干态|{Z_j^*}〉_q、多模复共轭相干态的相反态|{-Z_j^*}〉_q以及多模虚相干态|{iZ_j^*}〉_q的线性叠加所组成的第Ⅴ类三态叠加多模叠加态光场|ψ₅⁽³⁾〉_q.利用多模压缩态理论研究了态|ψ₅⁽³⁾〉_q中广义磁场分量的等幂次N次方Y压缩特性.结果发现:当压缩次数N=2p且p=2m(m=1,2,3,…,…)时,只要各模的初始相位φ_j(j=1,2,…,…,q)、态间的初始相位差(θ₁-θ₂)、(θ₁-θ₃)和(θ₂-θ₃)以及受各模的初始相位φ_j调制的各单模相干态光场的平均光子数之和 等分别满足一定的取值条件,则态|ψ₅⁽³⁾〉_q的广义磁场分量就可呈现出周期性变化的广义非线性等幂次4m次方Y压缩效应.     

态|Ψ(3)>q中广义电场分量的偶数次N次方Y压缩

构造了由多模复共轭虚相干态、多模复共轭虚相干态的相反态和多模复共轭相干态的线性叠加所组成的一种新型的三态叠加多模叠加态光场|Ψ⁽³⁾>_q.利用多模压缩态理论,研究了态|Ψ⁽³⁾>_q中广义电场分量的偶数次等幂次N次方Y压缩特性.结果发现:态|Ψ⁽³⁾>_q是一种典型的三态叠加多模非经典光场;当压缩次数N等于2P且P为2m’+1(m’=0,1,2,…,…)时,如果各模的初始相位φ_j(j=1,2,3,…,…,q)、态间的初始相位差(θ₁-θ₂)、(θ₁-θ₃)和(θ₂-θ₃),以及各单模相干态光场的总的平均光子数等分别满足各自的取值条件,则在这种情况下态|Ψ⁽³⁾>_q的广义电场分量可呈现出偶数次的广义非线性等幂次2(2m’+1)次方Y压缩效应.     

第Ⅴ类两态叠加多模叠加态光场的等阶N次方H压缩特性研究

本文构造了由多模真空态|{O_j}〉q和多模虚相干态的相反态|{-iZ_j}〉q这两者的线性叠加所组成的第Ⅴ类两态叠加多模叠加态光场ψ₅⁽²⁾〉q,利用多模压缩态理论详细研究了态 ψ₅⁽²⁾〉q的广义非线性等阶N次方H压缩特性.结果发现:1)态ψ₅⁽²⁾〉q是一种典型的多模非经典光场;无论腔模总数q与压缩阶数N这两者之积q·N取奇还是取偶,只要各模的初始相位之和 、态间的初始相位之差(θ_nq^(I)－θ_oq^(o))等满足一定的量子化条件,态ψ₅⁽²⁾〉q总可分别呈现出周期性变化的、任意的奇数模-奇数阶、奇数模-偶数阶、偶数模-偶数阶和偶数模-奇数阶这四种不同形式的等阶N次方H压缩效应.2)上述四种不同形式的等阶N次方H压缩效应,其态间压缩条件完全相同,但模间压缩条件完全不同,结果使其压缩幅度、压缩结果和压缩特性等各不相同.3)无论q·N取奇还是取偶,态ψ₅⁽²⁾〉q的第一和第二这两个正交分量的等阶N次方H压缩效应总是呈现周期性的互补关系.     

基于小波leaders的海杂波时变奇异谱分布分析

海杂波的奇异谱分析不仅能从理论上揭示海洋表面的动力学机理,同时也是对海探测雷达的关键技术之一.本文提出基于小波leaders的海杂波时变奇异谱分析方法,将时间信息引入海杂波的奇异谱分析之中,从而实现动态的解析描述海杂波随时间变化的奇异谱特性.在理论上,通过信号自身加窗,将时间信息引入传统的奇异谱(或称多重分形谱),实现了对海杂波时变奇异谱分布分析;在算法上,充分利用了小波leaders技术对于多种奇异性的提取能力(包括chirp奇异性和cusp奇异性),通过对时变奇异性指数和时变尺度函数的Legendre变换,实现对海杂波时变奇异谱分布的计算;在应用部分,采用经典的多重分形模型——随机小波序列(RWC)以及三级海态条件下连续波多普勒体制雷达海杂波进行仿真分析,实验结果表明:1)基于小波leaders的奇异谱分布能跟踪海杂波的时变尺度特性,有效展示其时变奇异性谱分布;2)算法具有较好的负矩特性和统计收敛性.该方法能为复杂非线性系统及随机多重分形信号分析提供参考.     

Relationships of exponents in multifractal detrended fluctuation analysis and conventional multifractal analysis

Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series. Although MF-DFA has become a widely used method, some relationships among the exponents established in the original paper seem to be incorrect under the general situation. In this paper, we theoretically and experimentally demonstrate the invalidity of the expression τ(q)=qh(q)-1 stipulating the relationship between the multifractal exponent τ(q) and the generalized Hurst exponent h(q). As a replacement, a general relationship is established on the basis of the universal multifractal formalism for the stationary series as τ(q)=qh(q)-qH'-1, where H' is the nonconservation parameter in the universal multifractal formalism. The singular spectra, α and f(α), are also derived according to this new relationship.     

Roughness and fractality of fracture surfaces as indicators of mechanical quantities of porous solids

The 3D profile surface parameter H _q and fractal dimension D were tested as indicators of mechanical properties inferred from fracture surfaces of porous solids. High porous hydrated cement pastes were used as prototypes of porous materials. Both the profile parameter H _q and the fractal dimension D showed capability to assess compressive strength from the fracture surfaces of hydrated pastes. From a practical point of view the 3D profile parameter H _q seems to be more convenient as an indicator of mechanical properties, as its values suffer much less from statistical scatter than those of fractal dimensions.     

混沌海杂波背景下的微弱信号检测混合算法

基于经验模态分解理论, 提出了一种基于粒子群算法的支持向量机预测方法. 采用总体平均经验模式分解法将混沌信号分解为若干固有模态函数和趋势分量, 将复杂的非线性信号转化为具有不同尺度特征的平稳分量. 利用粒子群算法对支持向量机的惩罚系数和核函数进行优化, 结合支持向量机建立混沌序列的单步预测模型. 从预测误差中检测淹没在混沌背景中的微弱信号(包括瞬态信号和周期信号). 对Lorenz系统和实测IPIX雷达数据进行仿真实验, 结果表明, 该方法能够有效地从混沌背景噪声中检测出微弱目标信号, Lorenz系统得到的均方根误差0.000000339 (-102.8225 dB时)比传统支持向量机方法的均方根误差0.049 (-54.60 dB时)降低了5个数量级, 从海杂波中检测出具有谐波特性的微弱信号, 表明预测模型具有更低的门限和误差.     

Diffusion on two-dimensional percolation clusters with multifractal jump probabilities

By means of Monte Carlo simulations we studied the properties of diffusion limited recombination reactions (DLRR's) and random walks on two dimensional incipient percolation clusters with multifractal jump probabilities. We claim that, for these kind of geometric and energetic heterogeneous substrata, the long time behavior of the particle density in a DLRR is determined by a random walk exponent. It is also suggested that the exploration of a random walk is compact. It is considered a general case of intersection ind euclidean dimension of a random fractal of dimension D_F and a multifractal distribution of probabilities of dimensionsD _q (q real), where the two dimensional incipient percolation clusters with multifractal jump probabilities are particular examples. We argue that the object formed by this intersection is a multifractal of dimensionsD' _q =D _q +D _F -d, for a finite interval ofq.     

Transition from fractal to non-fractal scalings in growing scale-free networks

Real networks can be classified into two categories: fractal networks and non-fractal networks. Here we introduce a unifying model for the two types of networks. Our model network is governed by a parameter q. We obtain the topological properties of the network including the degree distribution, average path length, diameter, fractal dimensions, and betweenness centrality distribution, which are controlled by parameter q. Interestingly, we show that by adjusting q, the networks undergo a transition from fractal to non-fractal scalings, and exhibit a crossover from ‘large’ to small worlds at the same time. Our research may shed some light on understanding the evolution and relationships of fractal and non-fractal networks.     

一种混沌海杂波背景下的微弱信号检测方法

基于复杂非线性系统的相空间重构理论,提出了一种基于遗传算法的支持向量机预测方法.利用改进的自相关法和饱和关联维数法确定混沌信号的时间延迟和嵌入维,从而实现相空间重构.通过遗传算法优化支持向量机中的惩罚系数和核函数参数,并结合支持向量机建立混沌序列的单步预测模型,从预测误差中检测出淹没在混沌背景中的微弱信号(包括瞬态信号和周期信号).以Lorenz系统和加拿大McMaster大学利用IPIX雷达实测得到的海杂波数据作为混沌背景噪声进行仿真实验,结果表明该方法能够有效地从混沌背景噪声中检测出微弱目标信号,所得的均方根误差为0.00049521(信噪比为-89.7704 dB),这比传统支持向量机方法的均方根误差(0.049,信噪比为-54.60 dB)降低了两个数量级.     

Thermodynamic and scaling behaviour in finite diffusion-limited aggregation

Rényi's entropies for diffusion-limited aggregates are studied as a function of the number N of particles contained in the aggregates. It is found that Rényi's values increase with log N in a linear fashion, and that the aggregates exhibit multifractal behaviour for finite values of N. When N → ∞, the aggregate has a monofractal structure. Rényi's entropies depend on the fractal dimension of the aggregate. When the fractal dimension increases, the values of K_q decrease for q ? 1> and increase for q > 1.     

On spurious and corrupted multifractality: The effects of additive noise, short-term memory and periodic trends

We study the performance of multifractal detrended fluctuation analysis (MF-DFA) applied to long-term correlated and multifractal data records in the presence of additive white noise, short-term memory and periodicities. Such additions and disturbances that can be typically found in the observational records of various complex systems ranging from climate dynamics to physiology, network traffic, and finance. In monofractal records, we find that (i) additive white noise hardly results in spurious multifractality, but causes underestimated generalized Hurst exponents h(q) for all q values; (ii) short-range correlations lead to pronounced crossovers in the generalized fluctuation functions F_q(s) at positions that decrease with increasing moment q, thus causing significantly overestimated h(q) for small q and spurious multifractality; (iii) periodicities like seasonal trends (with standard deviations comparable with the one of the studied process) result in spurious “reversed” multifractality where h(q) increases with increasing q (except for very short time windows). We also show that in multifractal cascades moderate additions of noise, short-range memory, or periodic trends cause flawed results for h(q) with q<2, while h(q) with q>2 remains nearly unchanged.