Extraction optimization, characterization and antioxidant activity in vitro of polysaccharides from mulberry leaves (MLP) were investigated in the present study. The optimal extraction conditions with an extraction yield of 10.0 ± 0.5% for MLP were determined as follows: extraction temperature 92 °C, extraction time 3.5h and ratio (v/w, mL/g) of extraction solvent (water) to raw material 34. Tw...

Inspired by both the multilayer perceptron (MLP) and wavelet decomposition, Zhang and Benveniste proposed the wavelet MLP (W-MLP), which has been usedfor time series prediction. The wavelet packet MLP (WP-MLP) is an MLP with the wavelet packet as a feature extraction method to obtain time-frequency information. The WPMLP has been successfully applied to biomedical, image and speech classificati...

Adverse left ventricular (LV) remodeling after myocardial infarction (MI) is a major cause for heart failure. Molecular modifiers of the remodeling process remain poorly defined. Patients with heart failure after MI have reduced LV expression levels of muscle LIM protein (MLP), a component of the sarcomeric Z-disk that is involved in the integration of stress signals in cardiomyocytes. By using...

Wind speed high-precision prediction is one of the most important technical aspects to protect the safety of wind power utilization. In this study, two new hybrid methods [FEEMD-MEA-MLP/FEEMD-GA-MLP] are proposed for the wind speed accurate multi-step predictions by combining FEEMD (Fast Ensemble Empirical Mode Decomposition), MEA (Mind Evolutionary Algorithm), GA (Genetic Algorithm) and MLP (M...

In this paper, we study a natural extension of Multi Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for numerical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to the one of numerical MLP. We obtain consistency results which imply that optimal parameters estimation f...

MOTIVATION Multilayer perceptrons (MLP) represent one of the widely used and effective machine learning methods currently applied to diagnostic classification based on high-dimensional genomic data. Since the dimensionalities of the existing genomic data often exceed the available sample sizes by orders of magnitude, the MLP performance may degrade owing to the curse of dimensionality and over-...