In this paper, we are discuss about the issue of synchronization for singular complex dynamical networks with Markovian jumping parameters and additive time-varying delays through pinning control by Takagi-Sugeno (T-S) fuzzy theory.The complex dynamical systems consist of m nodes and the systems switch from one mode to another, a Markovian chain with glorious transition probabili...

statistical process control (spc) charts play a major role in quality control systems, and their correct interpretation leads to discovering probable irregularities and errors of the production system. in this regard, various artificial neural networks have been developed to identify mainly singular patterns of spc charts, while having drawbacks in handling multiple concurrent patterns. in this...

Context: Recently, the singular points of neural networks have attracted attention from the artificial intelligence community, and their interesting properties have been demonstrated. The objective of this study is to provide an overview of studies on the singularities of complex-valued neural networks. Evidence Acquisition: This review is based on the relevant literature on complex-valued neur...

a novel algorithm for the fast detection of hubs in chemical networks is presented. thealgorithm identifies a set of nodes in the network as most significant, aimed to be the mosteffective points of distribution for fast, widespread coverage throughout the system. we showthat our hubs have in general greater closeness centrality and betweenness centrality thanvertices with maximal degree, while...

In this paper, the singularity and its effect on learning dynamics in the complex-valued neural network are elucidated. It has learned that the linear combination structure in the updating rule of the complex-valued neural network increases the speed of moving away from the singular points, and the complex-valued neural network cannot be easily influenced by the singular points, whereas the lea...

In this paper, the natural gradient descent method for the multilayer stochastic complex-valued neural networks is considered, and the natural gradient is given for a single stochastic complex-valued neuron as an example. Since the space of the learnable parameters of stochastic complex-valued neural networks is not the Euclidean space but a curved manifold, the complex-valued natural gradient ...

By a quasi-permutation matrix, we mean a square non-singular matrix over the complex field with non-negative integral trace....

a critical point is a point at which the derivatives of an error function are all zero. It has been shown in the literature that critical points caused by the hierarchical structure of a realvalued neural network (NN) can be local minima or saddle points, although most critical points caused by the hierarchical structure are saddle points in the case of complex-valued neural networks. Several s...