Local Temporal Correlation Common Spatial Patterns for Single Trial EEG Classification during Motor Imagery

Common spatial pattern (CSP) is one of the most popular and effective feature extraction methods for motor imagery-based braincomputer interface (BCI), but the inherent drawback of CSP is that the estimation of the covariance matrices is sensitive to noise. In this work, local temporal correlation (LTC) information was introduced to further improve the covariance matrices estimation (LTCCSP). Compared to the Euclidean distance used in a previous CSP variant named local temporal CSP (LTCSP), the correlation may be a more reasonable metric to measure the similarity of activated spatial patterns existing in motor imagery period. Numerical comparisons among CSP, LTCSP, and LTCCSP were quantitatively conducted on the simulated datasets by adding outliers to Dataset IVa of BCI Competition III and Dataset IIa of BCI Competition IV, respectively. Results showed that LTCCSP achieves the highest average classification accuracies in all the outliers occurrence frequencies. The application of the three methods to the EEG dataset recorded in our laboratory also demonstrated that LTCCSP achieves the highest average accuracy. The above results consistently indicate that LTCCSP would be a promising method for practical motor imagery BCI application

The Alteration of Runner and Partial Vanes on a Fixed Blade Propeller Water Turbine Basing on the Full Passage Simulation

ABSTRACT Basing on the 3D-steady Navier-Stokes equations with standard k-ε turbulence closure models, non-structure mesh with fitted body coordinate and finite element based finite volume method, the internal flow on the full passage of the 6.5-meters head fixed blade propeller water turbine is analyzed. Numerical results show that the low output is caused by unsuitable full passage. The flow on the stay vanes isn't uniform and the circumferential velocity of the runner rim is too large, which leads to a high loss in the draft tube. So the runner and partial stay vanes in the concrete spiral casing are redesigned. The output of the full passage with new runner and new partial stay vanes under 6.5-meters head is 295KW larger than the old one with 240KW output, and the efficiency is 81%, which is larger than former 70%. The redesign of runner and stay vanes is successful

FEDSM2009-78239 THE STUDY OF GUIDE VANES ON SUBMERSIBLE PUMP

ABSTRACT Because the structure of submersible pump is special, and common guide vane is a factor effecting low efficiency, those guide vanes design method is different from ones of common axial flow pump and mixed flow pump. This paper introduces the design methods of guide vane on submersible pump. To improve the total performance, submersible pump structure, hydraulic performance, diffusion and friction loss are considered comprehensively when the meridian plane of guide vane is designed. The coefficient of diffusion on meridian plane should be larger than the recommended value and limited to avoid heavy flow separation. The guide vane number is bigger and meridian length of guide vane is shortened. For example, the number of guide vane can be nine or eleven, even thirteen when impeller blade number is four. Bigger number of guide vane makes the short guide vane placed on smaller diameter and avoids flow passage diffused more. On the other hand, smaller diameter will decrease pump dimension, weight, and production cost. To Balance the recycled energy and loss energy, outlet angle of guide vane should be reduced suitable. The angle should be 90 degree if completely recycling the rotating flow energy, but outlet angle should be larger than 90 degree if considering finite cascade. Those two angles will bring large diffusion of flow passage, large diffusion loss and flow friction force. Since the diffusion loss counts heavier percent of hydraulic loss, the angle should be reduced, such as 70 degree. That smaller angle doesn't recycle completely the rotating energy, but hydraulic loss is decreased, and the efficiency of pump is higher instead. The test testifies that the efficiency of submersible pump designed by those above measures can reach 88%

Z-score linear discriminant analysis for EEG based brain-computer interfaces.

Linear discriminant analysis (LDA) is one of the most popular classification algorithms for brain-computer interfaces (BCI). LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enhanced version of LDA, namely z-score linear discriminant analysis (Z-LDA), which introduces a new decision boundary definition strategy to handle with the heteroscedastic class distributions. Z-LDA defines decision boundary through z-score utilizing both mean and standard deviation information of the projected data, which can adaptively adjust the decision boundary to fit for heteroscedastic distribution situation. Results derived from both simulation dataset and two actual BCI datasets consistently show that Z-LDA achieves significantly higher average classification accuracies than conventional LDA, indicating the superiority of the new proposed decision boundary definition strategy

Local Temporal Correlation Common Spatial Patterns for Single Trial EEG Classification during Motor Imagery

Common spatial pattern (CSP) is one of the most popular and effective feature extraction methods for motor imagery-based brain-computer interface (BCI), but the inherent drawback of CSP is that the estimation of the covariance matrices is sensitive to noise. In this work, local temporal correlation (LTC) information was introduced to further improve the covariance matrices estimation (LTCCSP). Compared to the Euclidean distance used in a previous CSP variant named local temporal CSP (LTCSP), the correlation may be a more reasonable metric to measure the similarity of activated spatial patterns existing in motor imagery period. Numerical comparisons among CSP, LTCSP, and LTCCSP were quantitatively conducted on the simulated datasets by adding outliers to Dataset IVa of BCI Competition III and Dataset IIa of BCI Competition IV, respectively. Results showed that LTCCSP achieves the highest average classification accuracies in all the outliers occurrence frequencies. The application of the three methods to the EEG dataset recorded in our laboratory also demonstrated that LTCCSP achieves the highest average accuracy. The above results consistently indicate that LTCCSP would be a promising method for practical motor imagery BCI application

Classification accuracies (%) comparison on Dataset IVa of BCI Competition III.

<p>Classification accuracies (%) comparison on Dataset IVa of BCI Competition III.</p

Distribution of the weight sum of subject 1.

<p>Blue dashed line is the Gaussian distribution curve according to the characteristic of weight sum with left hand motor imagery in training set; red dashed line is the Gaussian distribution curve according to the characteristic of weight sum with right hand motor imagery in training set; blue circles denote the weight sum with left hand motor imagery in test set; red stars denote the weight sum with right hand motor imagery in test set; blue solid line is the Gaussian distribution curve derived from the blue circles; red solid line is the Gaussian distribution curve derived from the red stars; green dashed vertical line is the decision boundary defined by LDA from training set; green solid vertical line is the decision boundary defined by Z-LDA from training set; black solid vertical line is the theoretical boundary of test set.</p