This paper focuses on the discussion of H ∞ synchronization in multiple state and delayed state coupled neural networks through the implementation of two adaptive proportional–integral (PI) controllers. Firstly, we consider two types of coupled ...

This paper has investigated the fixed/predefined-time synchronization problem of delayed memristive neural networks(DNNs). Firstly, two novel controllers with state variable index coefficient are presented for achieving fixed-time synchronization ...

As quaternion-valued memristor neural networks (MNNs) have important applications in many engineering fields and the information in the real world is often uncertain and inaccurate, therefore, in order to better apply to practice, it is necessary to study ...

A novel aperiodic event-triggered control is adopted to address the synchronization issue of T-S fuzzy neural networks with time delay. This control strategy refers to the execution of control tasks in a control system based on real-time events, rather ...

The problem of the globally asymptotical synchronization is studied for the system of fractional-order delayed octonion-valued BAM neural networks (FODOVBAMNNs) and the problem of the global Mittag–Leffler synchronization is researched for the ...

The synchronization problem of bidirectional associative memory memristive neural networks (BAMMNNs) with time-varying delays plays an essential role in the implementation and application of neural networks. Firstly, under the framework of the ...

This paper presents theoretical results on multiple asymptotical ω-periodicity of a state-dependent switching fractional-order neural network with time delays and sigmoidal activation functions. Firstly, by combining the geometrical ...

• Proposed a switched fractional-order neural network model.
• Proved the S-...

This paper focuses on comprehensive analysis of fixed-time stability and energy consumed by controller in nonlinear neural networks with time-varying delays. A sufficient condition is provided to assure fixed-time stability by ...

While Convolutional Neural Networks (CNNs) have significantly boosted the performance of face related algorithms, maintaining accuracy and efficiency simultaneously in practical use remains challenging. The state-of-the-art methods employ deeper ...

• Employ the structural information at shallow layer for efficient face alignment.
• Generate a heatmap to provide the geometric and attention information for network.
• Propose an efficient multitask framework for video-based ...

In this paper, a new case of neural networks called fractional-order octonion-valued bidirectional associative memory neural networks (FOOVBAMNNs) is established. First, the higher dimensional models are formulated for FOOVBAMNNs with ...

This paper focuses on finite-time exponential dissipative analysis and control problems for bidirectional associative memory neural networks (BAMNNs) with state-dependent switching and time-varying delays. Firstly, the state-dependent ...

This paper mainly focuses on the lag H ∞ synchronization problem of coupled neural networks with multiple state or delayed state couplings. On one hand, by exploiting state feedback controller and Lyapunov functional, a criterion of ...

This paper concentrates on trade off analysis between fixed-time stabilization and energy consumption for a type of nonlinear neural networks (NNs). By constructing a compound switching controller and utilizing inequality techniques, a ...

In this paper, lag projective synchronization of nonidentical fractional delayed memristive neural networks (NFDMNN) is investigated. Due to the existence of memristor, the analysis is based on the theory of differential equations with ...

This paper proposes the relaxed criteria about the problem of synchronization and stability for the same category fractional-order system of multidimension-valued neural networks (FOSMVNNs). First, we uniformly formulate a new class of ...

This paper presents the multistability analysis and associative memory of neural networks (NNs) with Morita-like activation functions. In order to seek larger memory capacity, this paper proposes Morita-like activation functions. In a ...

The paper considers the stability of coupled impulsive neural networks with time-varying delays and saturating actuators in finite time. Based on a delayed state feedback controller, the stability of coupled impulsive neural networks ...

This paper investigates mean square stabilization problem of neural networks with weighted try once discard protocol and state observer. In general, sensor nodes access conflict happens frequently in the communication transmission networks. Aiming ...

This pape investigates the global stabilization of memristive neural networks (MNNs) with leakage and time-varying delays via quantized sliding-mode controller. The leakage delay is considered in the MNNs. Sliding mode controller is imported to ...

Pulse-coupled neural network (PCNN) is a powerful unsupervised learning model with many parameters to be determined empirically. In particular, the weight matrix is invariable in the iterative process, which is inconsistent with the actual ...