Luk-Lindenbaum代数中的*滤子

从＊运算出发定义了＊滤子，利用格论的相关知识，对公式子集D（Г）进行研究。主要结果是：（1）Luk-Lin-denbaum代数F（S）／～中的＊滤子都是（D（Г））形式的；（2）＊滤子与MP滤子一致，都是通常意义下的滤子；（3）F（S）／～中的极大＊滤子与通常意义下的极大滤子是一致的。

MV代数中的*滤子

根据MV代数中伴随对(*,→)的定义,由二元运算*引入了*滤子的概念,证明了*滤子即是通常意义下的滤子,同时也研究了其*滤子的简单性质.

Implicative and Fuzzy Implicative Ideals of Lattice Implication Algebras

In this paper, we defined the concept of implicative and fuzzy implicative ideals of lattice implication algebras, and discussed the properties of them. And then, we pointed out the relations between implicative ideal and LI _ideal, implicative iedal and implicative filter, implicative ideal and fuzzy implicative ideal, fuzzy implicative ideal and fuzzy implicative filter, and fuzzy implicative ideal and fuzzy LI _ideal.

The Logical Properties of Filters of Lattice Implication Algebra

In this paper, we discuss some propertie s of lattice implication algebra and difine the transitivity of implication in a set, we show the transitivity of implication and the substitution Theorem hold i n filters. So every filter of lattice implication algebra satisfies the Syllogis m and substitution Theorem of propositional logic.

Hybrid particle filtering algorithm for GPS multipath mitigation

An altemative algorithm for mitigating GPS multipath was presented by integrating unscented Kalman filter （UKF） and wavelet transform with particle filter. Within consideration of particle degeneracy, UKF was taken for drawing particle. To remove the noise from raw data and data processing error, adaptive wavelet filtering with threshold was adopted while data preprocessing and drawing particle. Three algorithms, named EKF-PF, UKF-PF and WM-UKF-PF, were performed for comparison. The proposed WM-UKF-PF algorithm gives better error minimization, and significantly improves performance of multipath mitigation in terms of SNR and coefficient even though it has computation complexity. It is of significance for high-accuracy positioning and non-stationary deformation analysis.

Separation of Ions from Volatile Organic Compounds Using High-Field Asymmetric Waveform Ion Mobility Spectrometry-Mass Spectrometer

A combination of high-field asymmetric waveform ion mobility spectrometry （FAIMS） with mass spectrometer （MS） was analyzed. FAIMS separates ions from the volatile organic compounds in the gas-phase as an ion-filter for MS. The sample ions were created at ambient pressure by ion source, which was equipped with a 10.6 eV UV discharge lamp （A=116.5 nm）. The drift tube of FAIMS is composed of two parallel planar electrodes and the dimension is 10 mm×8 mm×0.5 mm. FAIMS was investigated when driven by the high-filed rectangular asymmetric waveform with the peak-to-peak voltage of 1.36 kV at the frequency of 1 MHz and the duty cycle of 30%. The acetone, the butanone, and their mixture were adopted to characterize the FAIMS-MS. The mass spectra obtained from MS illustrate that there are ion-molecular reactions between the ions and the sample neutral molecular. And the proton transfer behavior in the mixture of the acetone and the butanone is also observed. With the compensation voltage tuned from -30 V to 10 V with a step size of 0.1 V, the ion pre-separation before MS is realized.

Face tracking algorithm based on particle filter with mean shift importance sampling

The condensation tracking algorithm uses a prior transition probability as the proposal distribution, which does not make full use of the current observation. In order to overcome this shortcoming, a new face tracking algorithm based on particle filter with mean shift importance sampling is proposed. First, the coarse location of the face target is attained by the efficient mean shift tracker, and then the result is used to construct the proposal distribution for particle propagation. Because the particles obtained with this method can cluster around the true state region, particle efficiency is improved greatly. The experimental results show that the performance of the proposed algorithm is better than that of the standard condensation tracking algorithm.

Quantum stochastic filters for nonlinear time-domain filtering of communication signals

Principles and performances of quantum stochastic filters are studied for nonlinear time-domain filtering of communication signals. Filtering is realized by combining neural networks with the nonlinear Schroedinger equation and the time-variant probability density function of signals is estimated by solution of the equation. It is shown that obviously different performances can be achieved by the control of weight coefficients of potential fields. Based on this characteristic, a novel filtering algorithm is proposed, and utilizing this algorithm, the nonlinear waveform distortion of output signals and the denoising capability of the filters can be compromised. This will make the application of quantum stochastic filters be greatly extended, such as in applying the filters to the processing of communication signals. The predominant performance of quantum stochastic filters is shown by simulation results.

Multi-Parameter Design and Optimization for the Decomposition Projective Method and Its Applications

In order to solve the electromagnetic problems on the large multi branch domains, the decomposition projective method(DPM) is generalized for multi subspaces in this paper. Furthermore multi parameters are designed for DPM, which is called the fast DPM(FDPM), and the convergence ratio of the above algorithm is greatly increased. The examples show that the iterative number of the FDPM with optimal parameters decreases much more, which is less than one third of the DPM iteration number. After studying the ...

Isolation and Purification of Gonyautoxins from Two Strain of Alexandrium minutum Halim

Aim To study isolation and purification of Gonyautoxins from two differentstrains of Alexandrium minutum Halim. Methods Ethanol extracts of the two culture strains ofAlexandrium minutum Halim were fractionated by gel filtration and ion exchange chromatography toobtain gonyautoxins. The toxin profiles were tested by HPLC method. Results Both strains containgonyautoxin-1, gonyautoxin-2, gonyautoxin-3 and gonyautoxin-4. The total gonyautoxin content ofAmtk4 strain is almost 10 times higher than that of Amtk2 strain. Conclusion Alexandrium minutumHalim Amtk4 strain is suitable for the preparation of Gonyautoxins.

RESEARCH ON MEMBRANE BIOREACTOR TREATING DOMESTIC WASTEWATER AND RELATED MECHANISMS

Experiments on treatment of domestic wastewater by membrane bioreactors were carried out.The results showed that this process could produce good quality effluent with low COD,turbidity and total count of bacteria.With intermittent operation and continuous aeration,the membrane flux was kept steady.The mechanisms of removing COD through membrane,the structure of membrane and filtration resistance were also discussed.

Edge enhancement of gravity anomalies and gravity gradient tensors using an improved small sub-domain filtering method

In order to enhance geological body boundary visual effects in images and improve interpretation accuracy using gravity and magnetic field data, we propose an improved small sub-domain filtering method to enhance gravity anomalies and gravity gradient tensors. We discuss the effect of Gaussian white noise on the improved small sub-domain filtering method, as well as analyze the effect of window size on geological body edge recognition at different extension directions. Model experiments show that the improved small sub-domain filtering method is less affected by noise, filter window size, and geological body edge direction so it can more accurately depict geological body edges than the conventional small sub-domain filtering method. It also shows that deeply buried body edges can be well delineated through increasing the filter window size. In application, the enhanced gravity anomalies and calculated gravity gradient tensors of the Hulin basin show that the improved small sub-domain filtering can recognize more horizontal fault locations than the conventional method.

On Filters of Double MS-algebras

Here some properties on filters of double MS-algebras are descripted. We show that,for a normal filter F of a double MS-algebra (L;0, + )(x,y) ∈θ(F) (a,b ∈ F) (x ∧α)∨b+= (y ∧ a)∨ b+.

On Certain Filters in Lattice Implication Algebras

Lattice implication algebras is an algebraic structure which is established by combining lattice and implication algebras. In this paper, we introduce the concept of. I-feature filters and involutory filters in fat tice implication algebras, and discussed some propert ies of them. Finally, the characterization of filters of any lattice implication algebra which satisfies Increasing Chain Conditions (I. C. C) is given.

Experimental Research of DLC Film Deposited by Filtered Vacuum Arc Evaporation

Diamond like carbon (DLC) films was grown successfully on silicon, titanium and high speed steel (HSS) substrate at low temperature in a filtered vacuum arc deposition system. Arc discharges were established on a graphite cathode in this home built system with a toridal macroparticles filter. Ion current convected by the plasma beam was measured with a negatively biased probe. It was shown that the magnetic field of the coils located on the plasma duct has a strong influence on ion current. Scanning electron microscope (SEM), atomic force microscope (AFM) and Raman spectrum are used to study the DLC films. Tribological behaviors of the deposited film are also studied.

DCS devices based non-linear process control system design for plants with distributed time-delay using particle filter

Remote control process system with distributed time-delay has attracted much attention in different fields.In this paper,non-linear remote control of a single tank process system with wireless network is considered.To deal with the distributed time-delay in a large-scale plant,the time-delay compensation controller based on DCS devices is designed by using operator theory and particle filter.Distributed control system(DCS)device is developed to monitor and control from the central monitoring room to each process.The particle filter is a probabilistic method to estimate unobservable information from observable information.First,remote control system and experimental equipment are introduced.Second,control system based on an operator theory is designed.Then,process system with distributed time-delay using particle filter is carried out.Finally,the actual experiment is conducted by using the proposed time-delay compensation controller.When estimating with the proposed method,the result is close to the case in which the distributed time-delay does not exist.The effectiveness of the proposed control system is confirmed by experiment results.

Quasi-uniform itieson Lattice Im plication Algebras

We define a quasi uniformity on a lattice H implication algebra. We also introduce a quasi uniformity on any lattice implication algebra by using the set of filters.

Lattice Im plication Homom orphism inIm plication Filter Spaces

In this paper,we investigate some special properties of lattice implication homomorphism in implication filter spaces. We show that lattice implication homomorphism is a continuous function with respect to implication filter topology. Moreover,we give a structural characterstic of left translation topology and right translation topology,which finally leads to the structural characteristics of product topology.

METHOD OF CONSTRUCTING BORNOLOGICAL SPACES FROM L~*-VECTOR SPACES

A new method of constructing bornological vector topologies for vector spaces is discussed.In general,the convergent sequence and bounded set are concepts only in topological spaces.However,in this paper,it is first introduced sequential convergence C and L * space which is a vector space giving some relation:x mCx between sequences and points in it,then the bounded set is defined in vector space.Let C be a sequential convergence,T(C) be a vector topology on X determined by C and B(C) be the collection of bounded sets determined by C.Then B(C)=B(T(C)).Furthermore,the bornological locally convex topological vector space is constructed by L * vector space.

An Improved Gaussian Particle Filter Algorithm Using KLD-Sampling

To adjust the samples of filtering adaptively,an improved Gaussian particle filter algorithm based on Kullback-Leibler divergence(KLD)-sampling(KLGPF)is proposed in this paper.During the process of sampling,the algorithm calculates the KLD to adjust the size of the particle set between the discrete probability density function of particles and the true posterior probability density function.KLGPF has significant effect when the noise obeys Gaussian distribution and the statistical characteristics of noise change abruptly.Simulation results show that KLGPF could maintain a good estimation effect when the noise statistics changes abruptly.Compared with the particle filter algorithm using KLD-sampling(KLPF),the speed of KLGPF increases by 28%under the same conditions.