Lin Wang

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Because the relationship between electromyographic (EMG) signals and muscle activations remains unpredictable, a new way to determine muscle activations from EMG signals by using a neural network is proposed and realized. Using a neural network to predict the muscle activations from EMG signals avoids establishing a complex mathematical model to express the(More)
This paper introduces Gaborface-based 2DPCA and (2D) 2 PCA classification method based on 2D Gaborface matrices rather than transformed 1D feature vectors. Two kinds of strategies to use the bank of Gaborfaces are proposed: ensemble Gaborface representation (EGFR) and multichannel Gaborface representation (MGFR). The feasibility of our method is proved with(More)
In this paper, we propose a novel matching score normalization method for multi-classifiers based on their false acceptance rate (FAR) scores to make fusion operable at the matching level. The classifier discriminant analysis (CDA) is put forward and implemented to single out the best score from the appreciate classifier as the fusion output. Experimental(More)
Fusion different biometrics is an effective way to design a biometric system with robust performance. To do this, normalization functions are employed. However, these functions can not follow the distributions of scores from distinct classifiers. Consequently different normalization errors are introduced. In this paper, the scores from different classifiers(More)
Radical Basis Function (RBF) networks have been widely used in time series prediction because of their simplicity, robustness, good approximation and generalization ability. However, it is still rather difficult to select the number and locations of the hidden units of the RBF network appropriately for a specific time series prediction problem. In this(More)
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