This paper proposes a new structure of wavelet extreme learning machine i.e. an adaptive wavelet extreme learning machine (AW-ELM) for finger motion recognition using only two EMG channels. The adaptation mechanism is performed by adjusting the wavelet shape based on the input information. The performance of the proposed method is compared to ELM using wavelet (W-ELM0 and sigmoid (Sig-ELM) acti...

The study investigated predictive factors for best-corrected visual acuity (BCVA) after ranibizumab treatment in patients with macular edema (ME) associated with retinal vein occlusion (RVO) with an original ranking for the impairment of macular microstructure. In this retrospective study, 31 eyes of 31 patients with RVO received 3 monthly consecutive ranibizumab injections and another 3 months...

This paper proposes an approach to the identification of evolving fuzzy Takagi–Sugeno systems based on the optimally pruned extreme learning machine (OP-ELM) methodology. First, we describe ELM, a simple yet accurate learning algorithm for training single-hidden layer feed-forward artificial neural networks with random hidden neurons. We then describe the OP-ELM methodology for building ELM mod...

The Eukaryotic Linear Motif (ELM) resource (http://elm.eu.org) is a manually curated database of short linear motifs (SLiMs). In this update, we present the latest additions to this resource, along with more improvements to the web interface. ELM 2016 contains more than 240 different motif classes with over 2700 experimentally validated instances, manually curated from more than 2400 scientific...

In this paper, we describe an approximate method for reducing the time and memory complexities of the kernel Extreme Learning Machine variants. We show that, by adopting a Nyström-based kernel ELM matrix approximation, we can define an ELM space exploiting properties of the kernel ELM space that can be subsequently used to apply several optimization schemes proposed in the literature for ELM ne...

Extreme learning machine (ELM) is a type of randomized neural networks originally developed for linear classification and regression problems in the mid-2000s, has recently been extended to computational partial differential equations (PDE). This method can yield highly accurate solutions linear/nonlinear PDEs, but requires last hidden layer network be wide achieve high accuracy. If narrow, acc...

In this paper, an Optimally Pruned Extreme Learning Machine (OP-ELM) is applied to the problem of long-term time series prediction. Three known strategies for the long-term time series prediction i.e. Recursive, Direct and DirRec are considered in combination with OP-ELM and compared with a baseline linear least squares model and Least-Squares Support Vector Machines (LS-SVM). Among these three...

Linear motifs are short segments of multidomain proteins that provide regulatory functions independently of protein tertiary structure. Much of intracellular signalling passes through protein modifications at linear motifs. Many thousands of linear motif instances, most notably phosphorylation sites, have now been reported. Although clearly very abundant, linear motifs are difficult to predict ...