Computational intelligence and neuroscience
Jun 15, 2021
Networks are exposed to an increasing number of cyberattacks due to their vulnerabilities. So, cybersecurity strives to make networks as safe as possible, by introducing defense systems to detect any suspicious activities. However, firewalls and clas...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep con...
The field of neuroimaging can greatly benefit from building machine learning models to detect and predict diseases, and discover novel biomarkers, but much of the data collected at various organizations and research centers is unable to be shared due...
The tiny encryption algorithm (TEA) is widely used when performing dissipative particle dynamics (DPD) calculations in parallel, usually on distributed memory systems. In this research, we reduced the computational cost of the TEA hash function and i...
IEEE transactions on neural networks and learning systems
Apr 2, 2021
The article considers the impulsive synchronization for inertial neural networks with unbounded delay and actuator saturation via sampled-data control. Based on an impulsive differential inequality, the difficulties caused by unbounded delay and impu...
The Internet of Things (IoT) is permeating our daily lives through continuous environmental monitoring and data collection. The promise of low latency communication, enhanced security, and efficient bandwidth utilization lead to the shift from mobile...
Neural networks : the official journal of the International Neural Network Society
Jan 22, 2021
As deep neural net architectures minimize loss, they accumulate information in a hierarchy of learned representations that ultimately serve the network's final goal. Different architectures tackle this problem in slightly different ways, but all crea...
Neural networks : the official journal of the International Neural Network Society
Jan 20, 2021
In human-machine interfaces, decoder calibration is critical to enable an effective and seamless interaction with the machine. However, recalibration is often necessary as the decoder off-line predictive power does not generally imply ease-of-use, du...
Neural networks : the official journal of the International Neural Network Society
Jan 20, 2021
Deep neural networks (DNNs) with a complex structure and multiple nonlinear processing units have achieved great successes for feature learning in image and visualization analysis. Due to interpretability of the "black box" problem in DNNs, however, ...