the methods substantially differed with respect to the number of selected genes and the stability of selection. Of the analysed methods, the Boruta algorithm predicted the most genes as potentially important.
Long-term changes in synaptic efficacy between neurons are thought to underlie learning and memory1and can be assessed with a synaptic Hebbian paradigm such as spike timing-dependent plasticity (STDP)2,3,4,5,6,7,8. In STDP, the occurrence of timing-dependent-long-term potentiation (tLTP) or...
Recently, deep learning models have attracted the attention of researchers of speaker recognition and other research areas. In the study [14] Convolutional Neural Network (CNN) and Long Short Memory Networks, respectively, showed superior performance than GMM and i-vector approaches in speaker recognit...
Commonly applied ARIMA based time series modeling approaches are hybrids derived from models of the same family, e.g., AR-GARCH—AR models with GARCH residuals or based on models with dissimilar assumptions, e.g., ARIMA and neural networks. In the case of energy load prediction, it is ...