AIMC Topic: Neural Networks, Computer

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Finite-Time Command-Filtered Composite Adaptive Neural Control of Uncertain Nonlinear Systems.

IEEE transactions on cybernetics
This article presents a new command-filtered composite adaptive neural control scheme for uncertain nonlinear systems. Compared with existing works, this approach focuses on achieving finite-time convergent composite adaptive control for the higher-o...

Resilient Delayed Impulsive Control for Consensus of Multiagent Networks Subject to Malicious Agents.

IEEE transactions on cybernetics
Impulsive control is widely applied to achieve the consensus of multiagent networks (MANs). It is noticed that malicious agents may have adverse effects on the global behaviors, which, however, are not taken into account in the literature. In this st...

KAT: A Knowledge Adversarial Training Method for Zero-Order Takagi-Sugeno-Kang Fuzzy Classifiers.

IEEE transactions on cybernetics
While input or output-perturbation-based adversarial training techniques have been exploited to enhance the generalization capability of a variety of nonfuzzy and fuzzy classifiers by means of dynamic regularization, their performance may perhaps be ...

Distributed Adaptive Containment Control for Coupled Reaction-Diffusion Neural Networks With Directed Topology.

IEEE transactions on cybernetics
In this article, we consider the problem of distributed adaptive leader-follower coordination of partial differential systems (i.e., reaction-diffusion neural networks, RDNNs) with directed communication topology in the case of multiple leaders. Diff...

Delay-Dependent Stability Analysis for Switched Stochastic Networks With Proportional Delay.

IEEE transactions on cybernetics
In this article, the issue of exponential stability (ES) is investigated for a class of switched stochastic neural networks (SSNNs) with proportional delay (PD). The key feature of PD is an unbounded time-varying delay. By considering the comparison ...

Neuroadaptive Finite-Time Control for Nonlinear MIMO Systems With Input Constraint.

IEEE transactions on cybernetics
This article considers the problem of finite-time (FT) tracking control for a class of uncertain multi-input-multioutput (MIMO) nonlinear systems with input backlash. A modified FT command filter is designed in each step of backstepping, which ensure...

Projective Synchronization Analysis of Fractional-Order Neural Networks With Mixed Time Delays.

IEEE transactions on cybernetics
In this article, we analyze the projective synchronization of fractional-order neural networks with mixed time delays. By introducing an extended Halanay inequality that is applicable for the case of fractional differential equations with arbitrary i...

Breast Cancer Detection and Classification Empowered With Transfer Learning.

Frontiers in public health
Cancer is a major public health issue in the modern world. Breast cancer is a type of cancer that starts in the breast and spreads to other parts of the body. One of the most common types of cancer that kill women is breast cancer. When cells become ...

A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal.

BioMed research international
Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These arrhythmias can lead to potentially deadly consequences, putting your life in jeopardy. As a result, arrhythmia identification and classification are a...

Art Painting Image Classification Based on Neural Network.

Computational intelligence and neuroscience
Neural network (NN) is among the most important and vital form of artificial intelligence which are utilized for the classification of data, information, or images. Moreover, NN has been extensively utilized in various research domains throughout the...