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In this paper, we propose an improved learning algorithm named self-adaptive evolutionary extreme learning machine (SaE-ELM) for single hidden layer feedforward networks (SLFNs). In SaE-ELM, the network hidden node parameters are optimized by the self-adaptive differential evolution algorithm, whose trial vector generation strategies and their associated(More)
In this paper, we introduce a new learning method for composite function wavelet neural networks (CFWNN) by combining the differential evolution (DE) algorithm with extreme learning machine (ELM), in short, as CWN-E-ELM. The recently proposed CFWNN trained with ELM (CFWNN-ELM) has several promising features. But the CFWNN-ELM may have some redundant nodes(More)
Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually(More)
This paper provides improved time delay-dependent stability criteria for multi-input and multi-output (MIMO) network control systems (NCSs) with nonlinear perturbations. Without the stability assumption on the neutral operator after the descriptor approach, the new proposed stability theory is less conservative than the existing stability condition.(More)