Generalized variational principles for boundary value problem of electromagnetic field in electrodynamics

An expression of the generalized principle of virtual work for the boundary value problem of the linear and anisotropic electromagnetic field is given. Using Chien＇s method, a pair of generalized variational principles （GVPs） are established, which directly leads to all four Maxwell＇s equations, two intensity-potential equations, two constitutive equations, and eight boundary conditions. A family of constrained variational principles is derived sequentially. As additional verifications, two degenerated forms are obtained, equivalent to two known variational principles. Two modified GVPs are given to provide the hybrid finite element models for the present problem.

Mixing matrix estimation of underdetermined blind source separation based on the linear aggregation characteristic of observation signals

Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.

Study on local temperature characteristics of fiber Bragg gratings

The characteristics of fiber Bragg gratings(FBG) at local temperature are investigated based on the transfer matrix method.The reflective spectrum model of the FBG at local temperature is analyzed by theoretics and simulations.The results show that when a small section of the FBG is affected by the temperature variation,the reflective spectrum splits into two main peaks.The wavelength of the splitting point shifts linearly and periodically with the local temperature on the FBG.An experiment is also presented,and its results are agreement with the simulations.

Molecular Dynamics Simulation： Influence of External Electric Field on Bubble Interface in Air Flotation Process

Molecular dynamics（MD） simulation was performed to investigate the influence of external electric field on the vapottr-liquid interface of the bubble during the process of toluene separation by air flotation. The physico- chemical properties of vapour-liquid interface, surface tension, probability of a hydrogen bonding near the vapour- liquid interface and the viscosity of liquid phase caused by external electric field were analyzed. The results show that the angle between the water molecule dipole moment and the normal z axis in the vapour phase changes smaller when the external electric field is applied. The surface tension and the probability of hydrogen bonding near the vapour-liquid interface increase with the increase of electric field strength. And the viscosity also increases tinder an external electric field. The results confirm that the external electric field has a positive effect on the performance of bubbles in air flotation, which may provide useful guidance for the combination of electric field and air flotation technology.

Composite multiscale coherence and application to functionalcorticomuscular coupling

Though coherence, a classical method to describe the linear correlation between two time series, has wideranging applications, from economics to neuroscience, it fails to illustrate the inherently multi-time scalesbased correlations. In this paper, we proposed a multiscale-like coherence model, defined as composite multiscalecoherence (CMSC) by combining the kth coarse-grain processing with the coherence. We made a comparison withthe multiscale coherence (MSC) with coarse-grain process in numerical data to compare the sensitivity profiles tothe coupling strength, data length and white Gaussian noise. After that, we applied the proposed model to explorethe functional corticomuscular coupling (FCMC) by analyzing the correlation between the EEG and EMG signals.Simulation results reflected that the CMSC method were sensitive to the coupling strength, data length and thewhite Gaussian noise, and presented more stability along the time scale compared to the MSC method. Ourapplication of CMSC methods on the EEG and EMG signals indicated that the FCMC was of multi-time scalecharacteristics and higher coherence mainly consisted in the alpha and beta bands at about scale 10, thoughsignificant area showed a gradual decline with the scale increasing. Further comparison indicated that bothmodels are equally effective to describe the multiscale characteristics of the FCMC at lower time scales, whilesome differences emerge at the high time scales. Both simulation and experimental data demonstrate the effectiveness of the proposed multiscale-like model to describe the multiscale correlation between two time series. Thisstudy extends the relative researches on the FCMC to the multi-time scale.