In this paper, a novel approach to fuzzy sampled-data control of chaotic systems is presented by using a time-dependent Lyapunov functional. The advantage of the new method is that the Lyapunov functional is continuous at sampling times but not neces...
IEEE transactions on neural networks and learning systems
Jul 21, 2014
Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predict...
IEEE transactions on neural networks and learning systems
Jul 15, 2014
In this paper, adaptive neural control is investigated for a class of unknown multiple-input multiple-output nonlinear systems with time-varying asymmetric output constraints. To ensure constraint satisfaction, we employ a system transformation techn...
IEEE transactions on neural networks and learning systems
Jul 10, 2014
Kernel association (KA) in statistical pattern recognition used for classification and prediction have recently emerged in a machine learning and signal processing context. This survey outlines the latest trends and innovations of a kernel framework ...
A better understanding of cortical modifications related to movement preparation and execution after robot-assisted training could aid in refining rehabilitation therapy protocols for stroke patients. Electroencephalography (EEG) modifications of cor...
Decoding and classification of objects through task-oriented electroencephalographic (EEG) signals are the most crucial goals of recent researches conducted mainly for brain-computer interface applications. In this study we aimed to classify single-t...
PURPOSE: Conventional therapies for obstructive sleep apnea (OSA) are effective but suffer from poor patient adherence and may not fully alleviate major OSA-associated cardiovascular risk factors or improve certain aspects of quality of life. Predict...
IEEE journal of biomedical and health informatics
Apr 2, 2014
This paper evaluates the classification of multisample problems, such as electromyographic (EMG) data, by making aggregate features available to a per-sample classifier. It is found that the accuracy of this approach is superior to that of traditiona...
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Jan 20, 2026
OBJECTIVES: To enhance the accuracy and reliability of 12-lead electrocardiogram (ECG) automatic diagnosis. METHODS: Herein we propose a 12-lead ECG automatic diagnosis model based on deep feature fusion (MRHL-ECGNet), which consists of a multi-scale...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Dec 25, 2025
Automated detection of myocardial infarction (MI) is crucial for preventing sudden cardiac death and enabling early intervention in cardiovascular diseases. This paper proposes a deep learning framework based on a lightweight convolutional neural net...
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