Computational intelligence and neuroscience
May 31, 2022
In industry, sensor-based monitoring of equipment or environment has become a necessity. Instead of using a single sensor, multi-sensor system is used to fully detect abnormalities in complex scenarios. Recently, physical models, signal processing te...
The deployment of artificial neural networks-based optical channel equalizers on edge-computing devices is critically important for the next generation of optical communication systems. However, this is still a highly challenging problem, mainly due ...
IEEE transactions on bio-medical engineering
May 19, 2022
There is a growing interest in neuromorphic hardware since it offers a more intuitive way to achieve bio-inspired algorithms. This paper presents a neuromorphic model for intelligently processing continuous electrocardiogram (ECG) signal. This model ...
Music information retrieval is of great interest in audio signal processing. However, relatively little attention has been paid to the playing techniques of musical instruments. This work proposes an automatic system for classifying guitar playing te...
Deep neural networks are widely used in pattern-recognition tasks for which a human-comprehensible, quantitative description of the data-generating process, cannot be obtained. While doing so, neural networks often produce an abstract (entangled and ...
At present, the global demand for lithium batteries is still in a high growth state, and the traditional lithium battery pole mill control system is still dominated by ARM (Artificial Intelligence Enhanced Computing), DSP (Digital Signal Processing),...
IEEE transactions on biomedical circuits and systems
May 9, 2022
With the advent of high-density micro-electrodes arrays, developing neural probes satisfying the real-time and stringent power-efficiency requirements becomes more challenging. A smart neural probe is an essential device in future neuroscientific res...
IEEE journal of biomedical and health informatics
May 5, 2022
Physiological signals are of great importance for clinical analysis but are prone to diverse interferences. To enable practical applications, biosignal quality issues, especially contaminants, need to be dealt with automated processes. For example, a...
IEEE transactions on neural networks and learning systems
May 2, 2022
Neuromorphic systems are a viable alternative to conventional systems for real-time tasks with constrained resources. Their low power consumption, compact hardware realization, and low-latency response characteristics are the key ingredients of such ...
IEEE transactions on neural networks and learning systems
May 2, 2022
Surface electromyography (sEMG) signals have been applied widely in prosthetic hand controlling. In the sEMG signal acquisition, wireless devices bring convenience, but also introduce signal missing due to interference or failure during data transmis...