AIMC Topic:
Computer Simulation

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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...

An Algorithm for Time Prediction Signal Interference Detection Based on the LSTM-SVM Model.

Computational intelligence and neuroscience
Interference detection is an important part of the electronic defense system. It is difficult to detect interference with the traditional method of extracting characteristic parameters for interference generated at the same frequency as the original ...

Machine learning models outperform manual result review for the identification of wrong blood in tube errors in complete blood count results.

International journal of laboratory hematology
INTRODUCTION: Wrong blood in tube (WBIT) errors are a significant patient-safety issue encountered by clinical laboratories. This study assessed the performance of machine learning models for the identification of WBIT errors affecting complete blood...

Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing.

Scientific reports
Here, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors (memTs) with an unconventional redox-gating mechanism are demonstrated. Our synaptic memT device using con...

Machine Vision and Intelligent Algorithm Based on Neural Network.

Computational intelligence and neuroscience
Neural network algorithms and intelligent algorithms are hot topics in the field of deep learning. In this study, the neural network algorithm and intelligence are optimized, and it is used in simulation experiments to improve the target image recogn...

Synchronization and state estimation for discrete-time coupled delayed complex-valued neural networks with random system parameters.

Neural networks : the official journal of the International Neural Network Society
In this paper, an array of discrete-time coupled complex-valued neural networks (CVNNs) with random system parameters and time-varying delays are introduced. The stochastic fluctuations of system parameters, which are characterized by a set of random...

Introducing a Novel Model-Free Multivariable Adaptive Neural Network Controller for Square MIMO Systems.

Sensors (Basel, Switzerland)
In this study, a novel Multivariable Adaptive Neural Network Controller (MANNC) is developed for coupled model-free n-input n-output systems. The learning algorithm of the proposed controller does not rely on the model of a system and uses only the h...

A Prediction Model of Health Development Based on Linear Sequential Extreme Learning Machine Algorithm Matrix.

Computational intelligence and neuroscience
The rapid development of social economy not only increases people's living pressure but also reduces people's health. Looking for a healthy development prediction model has become a domestic concern. Based on the analysis of the influencing factors o...

Effects of Integrated Fuzzy Logic PID Controller on Satellite Antenna Tracking System.

Computational intelligence and neuroscience
An electrical device that transforms the electricity into the waves of radio and vice versa is termed the antenna. Its main deployment is in the transmitter and receiver of the antenna. While transmission, the transmitter of radio at the extremities ...

Recurrent neural network to predict hyperelastic constitutive behaviors of the skeletal muscle.

Medical & biological engineering & computing
Hyperelastic constitutive laws have been commonly used to model the passive behavior of the human skeletal muscle. Despite many efforts, the use of accurate finite element formulations of hyperelastic constitutive laws is still time-consuming for a r...