AIMC Topic: Algorithms

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Performance-based robotic assistance during rhythmic arm exercises.

Journal of neuroengineering and rehabilitation
BACKGROUND: Rhythmic and discrete upper-limb movements are two fundamental motor primitives controlled by different neural pathways, at least partially. After stroke, both primitives can be impaired. Both conventional and robot-assisted therapies mai...

Maze learning by a hybrid brain-computer system.

Scientific reports
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the co...

Unsupervised detection of cancer driver mutations with parsimony-guided learning.

Nature genetics
Methods are needed to reliably prioritize biologically active driver mutations over inactive passengers in high-throughput sequencing cancer data sets. We present ParsSNP, an unsupervised functional impact predictor that is guided by parsimony. ParsS...

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

Sensors (Basel, Switzerland)
Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overhea...

New results on exponential synchronization of memristor-based neural networks with discontinuous neuron activations.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the exponential synchronization of delayed memristor-based neural networks (MNNs) with discontinuous activation functions. Based on the framework of Filippov solution and differential inclusion theory, using new analytical tec...

A neurodynamic approach to convex optimization problems with general constraint.

Neural networks : the official journal of the International Neural Network Society
This paper presents a neurodynamic approach with a recurrent neural network for solving convex optimization problems with general constraint. It is proved that for any initial point, the state of the proposed neural network reaches the constraint set...

Classification of the fragrant styles and evaluation of the aromatic quality of flue-cured tobacco leaves by machine-learning methods.

Journal of bioinformatics and computational biology
During commercial transactions, the quality of flue-cured tobacco leaves must be characterized efficiently, and the evaluation system should be easily transferable across different traders. However, there are over 3000 chemical compounds in flue-cure...

Single NMR image super-resolution based on extreme learning machine.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
INTRODUCTION: The performance limitation of MRI equipment and higher resolution demand of NMR images from radiologists have formed a strong contrast. Therefore, it is important to study the super resolution algorithm suitable for NMR images, using lo...

ROCS-derived features for virtual screening.

Journal of computer-aided molecular design
Rapid overlay of chemical structures (ROCS) is a standard tool for the calculation of 3D shape and chemical ("color") similarity. ROCS uses unweighted sums to combine many aspects of similarity, yielding parameter-free models for virtual screening. I...

Fault Diagnosis for Analog Circuits by Using EEMD, Relative Entropy, and ELM.

Computational intelligence and neuroscience
This paper presents a novel fault diagnosis method for analog circuits using ensemble empirical mode decomposition (EEMD), relative entropy, and extreme learning machine (ELM). First, nominal and faulty response waveforms of a circuit are measured, r...