AIMC Topic: Neural Networks, Computer

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Vulnerability-oriented directed fuzzing for binary programs.

Scientific reports
Directed greybox fuzzing (DGF) is an effective method to detect vulnerabilities of the specified target code. Nevertheless, there are three main issues in the existing DGFs. First, the target vulnerable code of the DGFs needs to be manually selected,...

Towards accurate facial nerve segmentation with decoupling optimization.

Physics in medicine and biology
Robotic cochlear implantation is an effective way to restore the hearing of hearing-impaired patients, and facial nerve recognition is the key to the operation. However, accurate facial nerve segmentation is a challenging task, mainly for two key iss...

Event-Driven Off-Policy Reinforcement Learning for Control of Interconnected Systems.

IEEE transactions on cybernetics
In this article, we introduce a novel approximate optimal decentralized control scheme for uncertain input-affine nonlinear-interconnected systems. In the proposed scheme, we design a controller and an event-triggering mechanism (ETM) at each subsyst...

Neural-Network Adaptive Output-Feedback Saturation Control for Uncertain Active Suspension Systems.

IEEE transactions on cybernetics
The adaptive neural-network (NN) output-feedback control problem is investigated for a quarter-car active suspension system. The sprung mass and the suspension stiffness in the considered suspension system are unknown, and the part states are not mea...

Finite-Time Dynamic Allocation and Control in Multiagent Coordination for Target Tracking.

IEEE transactions on cybernetics
A new finite-time dynamic allocation and control scheme is developed in this article for multiple agents tracking a moving target. Based on a competitive manner, the dynamic allocation is achieved by k-winners-take-all (k-WTA), which can be realized ...

Memristor Neural Networks for Linear and Quadratic Programming Problems.

IEEE transactions on cybernetics
This article introduces a new class of memristor neural networks (NNs) for solving, in real-time, quadratic programming (QP) and linear programming (LP) problems. The networks, which are called memristor programming NNs (MPNNs), use a set of filament...

Polynomial Lyapunov Functions for Synchronization of Nonlinearly Coupled Complex Networks.

IEEE transactions on cybernetics
In this article, we search for polynomial Lyapunov functions beyond the quadratic form to investigate the synchronization problems of nonlinearly coupled complex networks. First, with a relaxed assumption than the quadratic condition, a synchronizati...

Finite-Time H Estimator Design for Switched Discrete-Time Delayed Neural Networks With Event-Triggered Strategy.

IEEE transactions on cybernetics
This article is concerned with the event-triggered finite-time H estimator design for a class of discrete-time switched neural networks (SNNs) with mixed time delays and packet dropouts. To further reduce the data transmission, both the measured info...

Asynchronous Distributed Finite-Time H Filtering in Sensor Networks With Hidden Markovian Switching and Two-Channel Stochastic Attack.

IEEE transactions on cybernetics
This article investigates the asynchronous distributed finite-time H filtering problem for nonlinear Markov jump systems over sensor networks under stochastic attacks. The stochastic attacks, called two-channel deception attacks, exist not only betwe...

System Transformation-Based Neural Control for Full-State-Constrained Pure-Feedback Systems via Disturbance Observer.

IEEE transactions on cybernetics
In this article, a novel disturbance observer-based adaptive neural control (ANC) scheme is proposed for full-state-constrained pure-feedback nonlinear systems using a new system transformation method. A nonlinear transformation function in a uniform...