高效前缀约简的三维Hilbert空间填充曲线编解码算法

3维Hilbert空间填充曲线(3D HSFC)的编码和解码效率对空间查询处理、图像处理等领域的应用举足轻重。现有的3维编解码算法独立编解码每一个点,忽略了Hilbert曲线的局部保持特性。为了提高编解码效率,该文设计了高效的3D状态视图,并提出一种新的前缀约简的3D HSFC编码算法(PR-3HE)和前缀约简3D HSFC解码算法(PR-3HD),这两个算法通过公共前缀的定义和识别、公共前缀约简及多种优化技术来最小化需要编码的阶数,从而提高3D HSFC的编解码效率。理论上证明:当编码或解码一个k阶的窗体(窗体内总共含有2k×2k×2k个点)时,PR-3HE平均每个点的编码阶数不超过2,PR-3HD平均解码阶数不超过8/7。相对于传统的基于迭代的方法,编解码时间复杂度从O(k)降低到了O(1)。实验结果表明,该文算法在模拟数据集和真实数据集上的表现显著优于现有算法。

q–differ-integral operator on p–valent functions associated with operator on Hilbert space

Making use of multivalent functions with negative coefficients of the type f (z)=z^(p)-~(∑)_(k=p+1)^(∞)a_(k)z^(k),which are analytic in the open unit disk and applying the q-derivative a q–differintegral operator is considered.Furthermore by using the familiar Riesz-Dunford integral,a linear operator on Hilbert space H is introduced.A new subclass of p-valent functions related to an operator on H is defined.Coefficient estimate,distortion bound and extreme points are obtained.The convolution-preserving property is also investigated.

New construction of mutually unbiased bases for odd-dimensional state space

We study the construction of mutually unbiased bases in Hilbert space for composite dimensions d which are not prime powers.We explore the results for composite dimensions which are true for prime power dimensions.We then provide a method for selecting mutually unbiased vectors from the eigenvectors of generalized Pauli matrices to construct mutually unbiased bases.In particular,we present four mutually unbiased bases in C^(15).

基于Hilbert空间向量赋权的网络选择算法

为了提升海上异构无线网络中移动节点业务完成率和网络资源配置效率,针对现有网络选择算法与业务需求匹配性较差、动态环境下业务完成率不高的问题,该文提出一种基于Hilbert空间向量赋权的网络接入选择算法。该算法采用基于Hilbert空间的网络-业务匹配模型,将网络特征与业务需求映射至同一空间,在同一坐标系内衡量网络是否满足业务需求;同时,采用基于优劣解距离法的预切换网络选择算法,引入网络-业务匹配权重对优劣解距离法标准化矩阵进行修正,确保所选网络与业务需求相匹配,克服传统网络选择中业务需求考虑较少、网络特征与业务需求难以进行统一衡量的问题。此外,采用基于空间距离的网络切换控制算法,将匹配权重、空间距离引入网络切换控制,保证业务传输连续性,提高动态环境下的业务完成率。仿真结果表明,相较于对比算法,该算法的业务平均完成率提高6.81%以上,有效提升了网络的业务传输能力和通畅度,间接实现了网络资源的有效配置。

加权Hilbert型空间中超齐次核离散算子的最佳搭配参数及范数计算

引入超齐次核概念,利用权系数方法,讨论具有超齐次核离散算子在加权Hilbert型空间中的有界性及算子范数,得到该类算子最佳搭配参数的充分必要条件和算子范数的计算公式,统一了齐次核,广义齐次核及若干非齐次核情形的相关结果.

Hilbert空间中Riesz-型框架的刻画

研究了Hilbert空间中Riesz-型框架的一些性质,给出了连续框架成为Riesz-型框架的一些等价条件,证明Hilbert空间中任意两个Riesz-型Parseval连续框架酉等价,进而证明了Hilbert空间中任意两个Riesz-型框架相似,最后通过引入由两连续Bessel序列诱导的有界线性算子进一步刻画了Riesz-型框架的等价性。

指数权的加权Lebesgue空间中拟齐次核最优Hilbert型积分不等式的参数条件及应用

首先,引入拟齐次核的概念,讨论权函数为指数函数的加权Lebesgue空间中具有拟齐次核的Hilbert型积分不等式;其次,利用权系数方法及若干分析技巧,给出最优Hilbert型积分不等式的等价参数条件,并获得了最佳常数因子的计算公式;最后,讨论其在算子理论中的应用.

Perturbations of Generalized Frames in a Hilbert Space

In the paper, we study the stability of Hilbert space generalized frames under perturbations. We get some results that are in spirit close to classical results for discrete frames, due to OLE Christensen.

GENERALIZED EXPANSIONS IN HILBERT SPACE

In this paper the authors give a definite meaning to any formal trigonometrical series and generalize it to all abstract Hilbert space. Then in the case L-2(-infinity + infinity) they discussed extensively the generalized expansion problem by Hermite functions, and applied to a non-strictly nonlinear hyperbolic system.

ON LINEAR EXTENSION OF 1-LIPSCHITZ MAPPING FROM HILBERT SPACE INTO A NORMED SPACE

In this article, we prove that an into 1-Lipschitz mapping from the unit sphere of a Hilbert space to the unit sphere of an arbitrary normed space, which under some conditions, can be extended to be a linear isometry on the whole space.

CERTAIN SUBCLASSES OF ANALYTIC p－VALENT FUNCTIONS FOR OPERATORS ON HILBERT SPACE

In this paper,We mainly discuss some subclasses of analytic functions for operators onac, and determine a representation formula and sufficient condition for the class 4;(a.p,r,E,7) and prove a sufficient and necessary condition.coefficient estimates and distortiontheorem for the subclass O;o (a,p,Y,e,9) of the class ac;(a,p,y,c,V).Furthermore,the analogues also are true for operators on Hilbert space.

An Interpretable Denoising Layer for Neural Networks Based on Reproducing Kernel Hilbert Space and its Application in Machine Fault Diagnosis

Deep learning algorithms based on neural networks make remarkable achievements in machine fault diagnosis,while the noise mixed in measured signals harms the prediction accuracy of networks.Existing denoising methods in neural networks,such as using complex network architectures and introducing sparse techniques,always suffer from the difficulty of estimating hyperparameters and the lack of physical interpretability.To address this issue,this paper proposes a novel interpretable denoising layer based on reproducing kernel Hilbert space(RKHS)as the first layer for standard neural networks,with the aim to combine the advantages of both traditional signal processing technology with physical interpretation and network modeling strategy with parameter adaption.By investigating the influencing mechanism of parameters on the regularization procedure in RKHS,the key parameter that dynamically controls the signal smoothness with low computational cost is selected as the only trainable parameter of the proposed layer.Besides,the forward and backward propagation algorithms of the designed layer are formulated to ensure that the selected parameter can be automatically updated together with other parameters in the neural network.Moreover,exponential and piecewise functions are introduced in the weight updating process to keep the trainable weight within a reasonable range and avoid the ill-conditioned problem.Experiment studies verify the effectiveness and compatibility of the proposed layer design method in intelligent fault diagnosis of machinery in noisy environments.

Perturbation and robust controllability of singular distributed parameter control systems in Hilbert space

Perturbation and robust controllability of the singular distributed parameter control system are discussed via functional analysis and the theory of GE-semigroup in Hilbert space. The perturbation principle of GE-semigroup and the sufficient condition concerning the robust controllability of the singular distributed parameter control system are obtained, in which the controllability for singular distributed parameter control system is not destroyed, if we perturb the equation by small bounded linear operator.

GENERAL SPLIT FEASIBILITY PROBLEMS FOR TWO FAMILIES OF NONEXPANSIVE MAPPINGS IN HILBERT SPACES

The purpose of this article is to introduce a general split feasibility problems for two families of nonexpansive mappings in Hilbert spaces. We prove that the sequence generated by the proposed new algorithm converges strongly to a solution of the general split feasibility problem. Our results extend and improve some recent known results.

Precise asymptotics in the law of the logarithm for random fields in Hilbert space

Consider the positive d-dimensional lattice Z^d（d≥2） with partial ordering ≤, let {XK; K∈Z＋^d} be i.i.d, random variables taking values in a real separable Hilbert space （H, ｜｜·｜｜） with mean zero and covariance operator ∑ and set partial sums SN =∑K≤nXK,K,N∈Z＋^d. Under some moment conditions, we obtain the precise asymptotics of a kind of weighted infinite series for partial sums SN as ε↓ by using the truncation and approximation methods. The results are related to the convergence rates of the law of the logarithm in Hilbert space, and they also extend the results of （Gut and Spataru, 2003）.

Loewner Chains Associated with the Generalized Roper-Suffridge Extension Operator on the Unit Ball in Hilbert Spaces

In this paper, we prove that the generalized Roper-Suffridge extension operator can be embeded in Loewner chains on the unit ball in Hibert spaces, and obtain the fact that the operator keeps the properties of almost spirallike mapping of typeβ and order α, almost starlikeness of order α, spirallikeness of type ofβ and starlikeness.

Minimax designs for linear regression models with bias in a reproducing kernel Hilbert space in a discrete set

Consider the design problem for estimation and extrapolation in approximately linear regression models with possible misspecification. The design space is a discrete set consisting of finitely many points, and the model bias comes from a reproducing kernel Hilbert space. Two different design criteria are proposed by applying the minimax approach for estimating the parameters of the regression response and extrapolating the regression response to points outside of the design space. A simulated annealing algorithm is applied to construct the minimax designs. These minimax designs are compared with the classical D-optimal designs and all-bias extrapolation designs. Numerical results indicate that the simulated annealing algorithm is feasible and the minimax designs are robust against bias caused by model misspecification.

AREA INTEGRAL FUNCTIONS AND H∞ FUNCTIONAL CALCULUS FOR SECTORIAL OPERATORS ON HILBERT SPACES

Area integral functions are introduced for sectorial operators on Hilbert spaces. We establish the equivalence relationship between the square and area integral functions. This immediately extends McIntosh/Yagi＇s results on H∞ functional calculus of sectorial operators on Hilbert spaces to the case when the square functions are replaced by the area integral functions.

Coarsely Invariant Hilbert Spaces over Infinite Connected Graphs

We study in this paper a Hilbert space HV associated with the coarse geometry of an infinite connected graph X(V, E) with vertex set V and edge set E. We show that X(V,E) is uniformly expanding if and only ifl2(V)can be continuously included in HV as a closed subspace,and that the inner product structure of HV is topologically invariant under uniform coarsening of the graph. We also discuss the functorial properties of these Hilbert spaces.

Amplitude-squared squeezing of the generalized odd-even coherent states of the anharmonic oscillator in a finite-dimensional Hilbert space

This paper discusses the properties of amplitude-squared squeezing of the generalized odd-even coherent states of anharmonic oscillator in finite-dimensional Hilbert space. It demonstrates that the generalized odd coherent states do exhibit strong amplitude-squared squeezing effects in comparison with the generalized even coherent states.