Abstract: This paper presents an efficient implementation of multivariate empirical mode decomposition (MEMD) algorithm, a multivariate extension of EMD algorithm. Analogous to EMD, MEMD decomposes a ...
WindowData() is a new function that allows users to segment data (univariate or multivariate time series) into windows with/without overlapping samples! This allows users to calculate entropy on ...
Accurately predicting the remaining mechanical equipment is of great significance for ensuring the safe operation of the equipment and improving economic efficiency. To accurately assess the ...
1 College of Computer Science and Engineering, Jishou University, Jishou, China. 2 College of Computer and Artificial Intelligence, Huaihua University, Huaihua, China. Extreme learning machine (ELM) ...
Divisive normalization is a ubiquitous computation commonly thought to be an implementation of the efficient coding principle. Despite empirical evidence that it reduces statistical redundancy present ...
This function uses an algorithm given in the paper "Numerical Computation of Multivariate Normal Probabilities", in J. of Computational and Graphical Stat., 1(1992), pp. 141-149, by Alan Genz, WSU ...
Due to the non-linearity of numerous physiological recordings, non-linear analysis of multi-channel signals has been extensively used in biomedical engineering and neuroscience. Multivariate ...
Poststroke fatigue affects a large proportion of stroke survivors and is associated with a poor quality of life. In a recent trial, modafinil was shown to be an effective agent in reducing poststroke ...
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