Spectral entropy analysis of different alpha band rhythms in relation to hand motor imagery

The event-related desynchronization/synchronization(ERD/ERS) time courses of lower and upper alpha band rhythms during hand motor imagery are investigated respectively by Fourier Sectral Entropy (FSE) in this paper. By analyzing one group of BCI competition data, it was found that FSE within upper alpha band displays a pronounced increase and decrease over contralateral and ipsilateral brain areas respectively at the onset of hand motor imagery, which is corresponding to the antagonistic ERD/ERS patterns in previous studies. Different from the upper alpha activity pattern, FSE within lower alpha band displays a consistent increase over both two hemispheres hand representative areas. The preliminary results show that FSE could disclose the different behaviors of the upper and lower alpha band rhythms so that a new idea with the complexity measure is provided to characterize functional dissociation of lower and upper frequency alpha rhythms in relation to hand motor imagery.

Complexity analyses of multi-wing chaotic systems

The complexities of multi-wing chaotic systems based on the modified Chen system and a multi-segment quadratic function are investigated by employing the statistical complexity measure （SCM） and the spectral entropy （SE） algorithm. How to choose the parameters of the SCM and SE algorithms is discussed. The results show that the complexity of the multi-wing chaotic system does not increase as the number of wings increases, and it is consistent with the results of the Grassberger-Procaccia （GP） algorithm and the largest Lyapunov exponent （LLE） of the multi-wing chaotic system.

Water discharge variability of Changjiang(Yangtze) and Huanghe(Yellow) Rivers and its response to climatic changes

Influences of large-scale climatic phenomena, such as the E1Nifio/La Nifia-Southem Oscillation （ENSO） and the Pacific Decadal Oscillation （PDO）, on the temporal variations of the annual water discharge at the Lijin station in the Huanghe （Yellow） River and at the Datong station in the Changjiang （Yangtze） River were examined. Using the empirical mode decomposition-maximum entropy spectral analysis （EMD- MESA） method, the 2- to 3-year, 8- to 14-year, and 23-year cyclical variations of the annual water discharge at the two stations were discovered. Based on the analysis results, the hydrological time series on the inter- annual to interdecadal scales were constructed. The results indicate that from 1950 to 2011, a significant downward trend occurred in the natural annual water discharge in Huanghe River. However, the changes in water discharge in Changjiang River basin exhibited a slightly upward trend. It indicated that the changes in the river discharge in the Huanghe basin were driven primarily by precipitation. Other factors, such as the precipitation over the Changjiang River tributaries, ice melt and evaporation contributed much more to the increase in the Changjiang River basin. Especially, the impacts of the inter-annual and inter-decadal climate oscillations such as ENSO and PDO could change the long-term patterns of precipitation over the basins of the two major rivers. Generally, low amounts of basin-wide precipitation on interannual to interdecadal scales over the two rivers corresponded to most of the warm ENSO events and the warm phases of the PDO, and vice versa. The positive phases of the PDO and ENSO could lead to reduced precipitation and consequently affect the long-term scale water discharges at the two rivers.

A grey model with periodic term for sea-level analysis and its application to the Guangxi coast

A grey model with periodic term for sea-level analysis is presented.The present model keeps some advantages of tea GM (1, 1 )model, which well reflects the trend of sea-level changes and gives out the change rate as well as the acceleration of sea level conveniently.level conveniently.In addition, the present model can reproduce the periodic phenomena of sealevel, hence, it overcomes the shortcomings of the GM(1,1) model that is unsuitable for forecasting monthly mean sealevel with apparent periodicity, and its prediction accuracy is improved.The present model is used to analyse Guangxi coast sea level,the results show that the rise rates of relative sea level at Beihai, Weizhou and Bailongwei are 1 .67,2 .51 and 0.89 mm/a respectively, the relative sea level at Shitoubu has a falling trend with a rate of 0. 5- 1 .0 mm/a, the rise rate of eustatic sea level along the Guangxi coast is 2 .0 mm/a. In comparison with the model with a lineartrend term plus a periodic term, the simulation accuracies of both models are about the same.

Detection and classification of multiple power signal patterns with Volterra series and interval type-2 fuzzy logic system

The paper deals with the application of Volterra bound Interval type−2 fuzzy logic techniques in power quality assessment.This work proposes a new layout for detection,localization and classification of various types of power quality events.The proposed method exploits Volterra series for the extraction of relevant features,which are used to recognize different PQ events by Interval type-2 fuzzy logic based classifier.Numerous single as well as multiple powers signal disturbances have been simulated to testify the efficiency of the proposed technique.This time–frequency analysis results in the clear visual detection,localization,and classification of the different power quality events.The simulation results signify that the proposed scheme has a higher recognition rate while classifying single and multiple power quality events unlike other methods.Finally,the proposed method is compared with SVM,feed forward neural network and type−1 Fuzzy logic system based classifier to show the efficacy of the proposed technique in classifying the Power quality events.