The traditional intelligent diagnosis methods for rolling bearing based on least squares
support vector machine (LS-SVM) need to manually extract sensitive features with …

Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic
learning modules, one after another, to synthesize a deep neural network (DNN) alternative …

The principal component analysis network (PCANet) is asserted as a parsimonious stacking-
based convolutional neural networks (CNNs) instance for generic object recognition …

Touch-stroke dynamics is an emerging behavioral biometrics justified feasible for mobile
identity management. A touch-stroke dynamics authentication system is composed of a hand …

Imaging flow cytometry is an attractive method to investigate individual cells by optical
properties. However, imaging flow cytometry applications with clinical relevance are scarce …

Extreme learning machine (ELM) is a popular method in machine learning with extremely
few parameters, fast learning speed and model efficiency. Unsupervised feature learning …

The development of data-driven process models based on bootstrap aggregated deep belief
networks (BAGDBN) is presented in this paper. In develo** a BAGDBN model, the original …

With the ever-increasing global competition and customer requirement, chemical industrial
processes face increasing pressure of maintaining high product quality and reducing …

In this study, a novel adaptive learning deep belief network (ALDBN) with a series of
growing and pruning algorithms is proposed to dynamically adjust its structure when ALDBN …

Abstract Extreme Learning Machine (ELM) is a popular method in machine learning with
extremely few parameters, fast learning speed and model efficiency. While a significant …