The adaptive fuzzy finite-time tracking control problem of a class of switched nonlinear
systems is investigated in this study. Fuzzy logic systems are introduced to handle the …

Maximum likelihood methods are based on the probability and statistics theory, and
significant for parameter estimation and system modeling. This paper combines the …

This paper considers the parameter identification problems of controlled autoregressive
systems using observation information. According to the hierarchical identification principle …

This paper proposes two nonlinear estimation approaches, namely based on Extended
Kalman Filter (EKF) and a Takagi-Sugeno Fuzzy Observer with 32 rules (TSFO-32), for a …

MRI is an advanced imaging modality with the unfortunate disadvantage of long data
acquisition time. To accelerate MR image acquisition while maintaining high image quality …

The chest X-ray examination is one of the most important methods for screening and
diagnosing of many lung diseases. Diagnosis of pneumonia by chest X-ray is one of the …

Accurate state-of-power (SOP) estimation is critical for building battery systems with
optimized performance and longer life in electric vehicles and hybrid electric vehicles. This …

In this article, we propose a new variant of evolving fuzzy model for regression problems,
which is based on error feedback integration in order to compensate measurement noise …

Abstract This paper demonstrates Robust Adaptive Control (RAC) approach using a
technique for system identification applied to a Buck (step-down) converter by PWM (Pulse …

Nowadays, despite the popularity of deep convolutional neural networks (CNNs), the
efficient training of network models remains challenging due to several problems. In this …