This work addresses an autonomous underwater vehicle (AUV) for applying nonlinear control which is capable of disturbance rejection via intelligent estimation of uncertainties. Adaptive radial basis function neural network (RBF NN) controller is proposed to approximate unknown nonlinear dynamics. The problem of designing an adaptive RBF NN controller was augmented with sliding mode robust term ...

This study deals with predicting nonlinear time history deflection of scallop domes subject to earthquake loading employing neural network technique. Scallop domes have alternate ridged and grooves that radiate from the centre. There are two main types of scallop domes, lattice and continuous, which the latticed type of scallop domes is considered in the present paper. Due to the large number o...

The aim of this paper is to fully analyze the effects of free space optical (FSO) communication links on the estimation performance of the adaptive incremental networks. The FSO links in this paper are described with two turbulence models namely the Log-normal and Gamma-Gamma distributions. In order to investigate the impact of these models we produced the link coefficients using these distribu...

In image denoising networks, feature scaling is widely used to enlarge the receptive field size and reduce computational costs. This practice, however, also leads loss of high-frequency information fails consider within-scale characteristics. Recently, dynamic convolution has exhibited powerful capabilities in processing (e.g., edges, corners, textures), but previous works lack sufficient spati...

Abstract Motivated by human behavior, dividing inpainting tasks into structure reconstruction and texture generation helps to simplify restoration process avoid distorted structures blurry textures. However, most of are ineffective for dealing with large continuous holes. In this paper, we devise a parallel adaptive guidance network(PAGN), which repairs enriches textures through branches, sever...