In recent years, neural networks have become a common practice in academia for handling
complex problems. Numerous studies have indicated that complex problems can generally …

For the purpose of enhancing the search ability of the cuckoo search (CS) algorithm, an
improved robust approach, called HS/CS, is put forward to address the optimization …

Using neural networks to handle intractability problems and solve complex computation
equations is becoming common practices in academia and industry. It has been shown that …

Three-dimensional dense reconstruction involves extracting the full shape and texture
details of three-dimensional objects from two-dimensional images. Although 3D …

Solving Sylvester equation is a common algebraic problem in mathematics and control
theory. Different from the traditional fixed-parameter recurrent neural networks, such as …

As a classical and effective method for solving various time-varying problems, the zeroing
neural network (ZNN) is widely applied in the scientific and industrial realms. In plentiful …

A correlation between fuzzy logic systems (FLS) and zeroing neural networks (ZNN) design
is investigated. It is shown that the gain parameter included in ZNN design can be …

In this paper, we propose a novel recurrent neural network to resolve the redundancy of
manipulators for efficient kinematic control in the presence of noises in a polynomial type …

The problem of solving linear equations is considered as one of the fundamental problems
commonly encountered in science and engineering. In this article, the complex-valued time …

Varying-parameter recurrent neural network, being a special kind of neural-dynamic
methodology, has revealed powerful abilities to handle various time-varying problems, such …