低幂平均列相关性测量矩阵构造算法

压缩感知是一种新的信号描述、采样和重构理论,其核心问题包括测量矩阵的选择和构造以及重构算法设计.本文首先提出感知矩阵幂平均列相关性定义,进而得出测量矩阵的择优原则;然后依据等角紧框架理论和特征向量近似法,提出新的测量矩阵构造算法,减小感知矩阵的幂平均列相关性.实验结果表明,本文算法达到了降低感知矩阵列相关性的目的.另外,当重构算法相同时,采用本文算法得到的测量矩阵比采用Gaussian、Elad、Xu和Vahid算法得到测量矩阵的重构错误率要低.

基于m序列的压缩感知测量矩阵构造

测量矩阵作为压缩感知理论的核心内容,对信号的测量和重构会产生重大影响。本文主要基于m序列构造压缩感知测量矩阵。首先,给出一种压缩率为0.5的测量矩阵构造方法,利用该方法构造的测量矩阵元素取值集合较小,具有一定的循环特性。其次,结合有限域的理论,对利用m序列构造的测量矩阵做进一步改进,改进后测量矩阵的压缩率取值范围增大加。仿真结果表明:本文构造的测量矩阵的重构性能优于同大小的Gause测量矩阵,避免了随机性测量矩阵的不确定性,具有一定实用价值。

Legendre序列测量矩阵的构造研究

测量矩阵是压缩感知理论的重要研究内容,对信号的测量和重构都有重大影响。理论上,随机性测量矩阵可以保证精确重构,但不能保证每一次都可以精确重构,且硬件实现复杂。从工程应用的角度来看,确定性测量矩阵更具有实际意义。文章利用legendre序列构造一种确定性的测量矩阵,根据legendre序列的自相关特性证明了该测量矩阵满足重构要求,并在此基础上加入了分块操作,进一步降低了实现的复杂性。仿真实验表明:该测量矩阵的重构性能高于同条件下的高斯测量矩阵,且避免了随机性测量矩阵的不确定性,具有一定实用价值。

MULTIVARIATE ABSOLUTE DEGREE OF GREY INCIDENCE BASED ON DISTRIBUTION CHARACTERISTICS OF POINTS

The analysis result of absolute degree of grey incidence for multivariate time series is often inconsistent with the qualitative analysis. To overcome this shortage, a multivariate absolute degree of grey incidence based on distribution characteristics of points is proposed. Based on the geometric description of multivariate time se- ries, the neighborhood extrema are extracted in the different regions, and a characteristic point set is constructed. Then according to the distribution of the characteristic point set, a characteristic point sequence reflecting the ge- ometric features of multivariate time series is obtained. The incidence analysis between multivariate time series is transformed into the relational analysis between characteristic point sequences, and a grey incidence model is established. The model possesses the properties of translational invariance, transpose and rank transform invari- ance, and satisfies the grey incidence analysis axioms. Finally, two cases are studied and the results prove the ef- fectiveness of the model.

RESEARCH ON PERFECT DYADIC BINARY SEQUENCE PAIR

In this paper, the perfect dyadic binary sequence pair with one-value dyadic correlation functions is presented. That is, the perfect dyadic binary sequence pair is a perfect discrete signal, for its dyadic relative function is δ-function. The transformation features and some existing admissibility conditions of perfect dyadic binary sequence pair are discussed, and the properties for this kind of code in Walsh transformation spectrum and weight spectrum are also analyzed. From above, It is found that the perfect dyadic binary sequence pair can easily differentiate from its dyadic shifting. So these good signals can used in engineering as synchronization code, multi-user code and so on.

Interval Sampling Method for Steady-State Simulation Output Analysis

A new algorithm namely the interval sampling method, applicable to the analysisof steady-state simulation output is proposed. This algorithm uses the time series analysisto carry out conrrelation analysis of the steady-state simulation output so as to obtain theobservation data which are actually uncorrelated in nature. On the basis of theseuncorrelated data gathered, some satisfactory deductions cam be made on the data under re search. A comparison between batch means method and the interval sampling method hasbeen performed by taking the M/M/l queuing system as an example. The results attestedthat the interval sampling method is mere accurate than the batch means method.

Analysis of SNR for Acoustic Vector Sensor Linear Array in Volume and Surface-generated Noise Fields

Acoustic vector sensor consists of pressure and particle velocity sensors,which measure the three-dimensional acoustic particle velocity,as well as the pressure at one location at the same time.By preserving the amplitude and phase information of the pressure and particle velocity,they possess a number of advantages over traditional scalar sensors.Signal-to-noise ratio (SNR) gain (which is often called array gain) is one of such advantages and is always interested by all of us.But it is not unchangeable if the spatial correlation of the noise field varies.Much more important,it is difficult to be given if the noise becomes complex.In this paper,spatial correlation of the vector field of isotropic volume-noise and surface-generated noise has been introduced briefly.Based on the results,the combined SNR output of a vector linear array is investigated and the maximum gain is given in the specified noise.Computer simulation shows that the output of one array in the same noise is not the same in different gestures.And then we find the best gesture through SNR calculation and obtain the biggest gain,which has important meaning to guide how to deploy an array in practice.We also should use the array with respect to the characteristics of the real ambient noise,especially in anisotropic noise field.

CROSS-CORRELATIONS BETWEEN QUADRATIC FORM SEQUENCES AND GEOMETRIC SEQUENCES OVER FINITE FIELDS

For all types of quadratic forms,the cross-correlations between geometric sequences and the newly defined quadratic form sequences are determined to extend the results presented by Klapper in 1993 and 1997.The technique for computing cross-correlations is based on counting the number of solutions for a system of equations that consists of a quadratic form and a linear function.

Sequence Analysis and Molecular Markers of a Copialike Retrotransposon Linked to the Color around the Stone(Cs) Locus of the Peach

Retrotransposons are present in all plant genomes and play important roles in genome size,genome structure remodeling,gene function and genome evolution.Me07Em02 marked by sequence-related amplified polymorphism (SRAP) is verified,recovered,sequenced and analyzed,which closely link to the flesh color around the stone.By comparison with the peach genome Peach v1.0,a part of the sequence of copia-like retrotransposons is obtained.With the aid of DANMAN and DNASTAR sequence analysis software,BLASTn alignment is carried out in the peach genome database and GenBank.The whole genome sequence of the copialike retrotransposon in the peach is located at 9 939 764~9 944 771 bp in Scaffold-1 of Peach v1.0,with a total length of 5 008 bp.The LTR on both sides is exactly the same,the length is 444 bp,and the largest ORF box is located at the 487~4 545 bp of the sequence,encoding 1 535 amino acids.The amino acid sequence was submitted to GenBank for Protein BLAST alignment,The results showed that this sequence also has the typical amino acid sequence characteristics of the copia-like retrotransposon.At the same time,the method of peach retrotransposon labeling is preliminarily established,and the genetic diversity of the peach is analyzed.

Dynamic multivariate multiscale entropy based analysis on brain death diagnosis

The recently introduced multivariate multiscale sample entropy(MMSE)well evaluates the long correlations in multiple channels,so that it can reveal the complexity of multivariate biological signals.The existing MMSE algorithm deals with short time series statically whereas long time series are common for real-time computation in practical use.As a solution,we novelly proposed our dynamic MMSE(DMMSE)as an extension of MMSE.This helps us gain greater insight into the complexity of each section of time series,producing multifaceted and more robust estimates than the standard MMSE.The simulation results illustrated the feasibility and well performance in the brain death diagnosis.

FAMILIES OF p-ARY SEQUENCES WITH LOW CORRELATION AND LARGE LINEAR COMPLEXITY

This paper generalizes a method of generating shift sequences in the interleaved construction proposed by Gong.With the new shift sequences,some new families of p-ary sequences with desired properties can be obtained.A lower bound on the number of new families of binary sequences is also established.

DEPENDENCE ANALYSIS OF REGRESSION MODELS IN TIME SERIES

In this paper, the relative dependence of a linear regression model is studied. In particular, the dependence of autoregressive models in time series are investigated. It is shown that for the first-order non-stationary autoregressive model and the random walk with trend and drift model, the dependence between two states decreases with lag. Some numerical examples are presented as well.

Strong Convergence for Weighted Sums of Negatively Associated Arrays

Let {Xni} be an array of rowwise negatively associated random variables and Tnk=k∑i=1 i^a Xni for a ≥ -1, Snk =∑｜i｜≤k Ф（i/nη）1/nη Xni for η∈（0,1],where Ф is some function. The author studies necessary and sufficient conditions of ∞∑n=1 AnP（max 1≤k≤n｜Tnk｜〉εBn）〈∞ and ∞∑n=1 CnP（max 0≤k≤mn｜Snk｜〉εDn）〈∞ for all ε 〉 0, where An, Bn, Cn and Dn are some positive constants, mn ∈ N with mn /nη →∞. The results of Lanzinger and Stadtmfiller in 2003 are extended from the i.i.d, case to the case of the negatively associated, not necessarily identically distributed random variables. Also, the result of Pruss in 2003 on independent variables reduces to a special case of the present paper; furthermore, the necessity part of his result is complemented.

HOPF ALGEBRAIC APPROACH TO THE n LINEARLY RECURSIVE SEQUENCES

It is proved that a linearly recursive sequence of n indices over field F (n≥1) is automatically a product of n linearly recursive sequences of 1-index over F by the theory of Hopf algebras.By the way, the correspondence between the set of linearly recursive sequences of 1-index and F[X]° is generalized to the case of n-index.

ZERO FINITE-ORDER SERIAL CORRELATION TEST IN A PARTIALLY LINEAR SINGLE-INDEX MODEL

The purpose of this paper is to test the underlying serial correlation in a partially linear single-index model. Under mild conditions, the proposed test statistics are shown to have standard chi- squared distribution asymptotically when there is no serial correlation in the error terms. To illustrate their finite sample properties, simulation experiments, as well as a real data example, are also provided. It is revealed that the finite sample performances of the proposed test statistics are satisfactory in terms of both estimated sizes and powers.

Underwater patch near-field acoustical holography based on particle velocity and vector hydrophone array

One-step patch near-field acoustical holography(PNAH) is a powerful tool for identifying noise sources from the partially known sound pressure field.The acoustical property to be reconstructed on the surface of interest is related to the partially measured pressure on the hologram surface in terms of sampling and bandlimiting matrices,which cost more in computation.A one-step procedure based on measuring of the normal component of the particle velocity is described,including the mathematical formulation.The numerical simulation shows that one-step PNAH based on particle velocity can obtain more accurately reconstructed results and it is also less sensitive to noise than the method based on pressure.These findings are confirmed by an underwater near-field acoustical holography experiment conducted with a vector hydrophone array.The experimental results have illustrated the high performance of one-step PNAH based on particle velocity in the reconstruction of sound field and the advantages of a vector hydrophone array in an underwater near-field measurement.