Neural networks : the official journal of the International Neural Network Society
Apr 6, 2018
We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse bi...
Neural networks : the official journal of the International Neural Network Society
Apr 6, 2018
Big high dimensional data is becoming a challenging field of research. There exist a lot of techniques which infer information. However, because of the curse of dimensionality, a necessary step is the dimensionality reduction (DR) of the information....
IEEE journal of biomedical and health informatics
Apr 5, 2018
Complexity, costs, and waiting list issues demand a simplified alternative for sleep apnea-hypopnea syndrome (SAHS) diagnosis. The blood oxygen saturation signal (SpO) carries useful information about SAHS and can be easily acquired from overnight ox...
In the EU brownfield presence is still considered a widespread problem. Even though, in the last decades, many research projects and initiatives developed a wealth of methods, guidelines, tools and technologies aimed at supporting brownfield regenera...
Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (M...
Automatic localization of organs and other structures in medical images is an important preprocessing step that can improve and speed up other algorithms such as organ segmentation, lesion detection, and registration. This work presents an efficient ...
The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (L...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 4, 2018
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...
Modeling and interpreting (partial) synchronous neural activity can be a challenge. We illustrate this by deriving the phase dynamics of two seminal neural mass models: the Wilson-Cowan firing rate model and the voltage-based Freeman model. We establ...
Neural networks : the official journal of the International Neural Network Society
Apr 4, 2018
Fractional order system is playing an increasingly important role in terms of both theory and applications. In this paper we investigate the global existence of Filippov solutions and the robust generalized Mittag-Leffler synchronization of fractiona...
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