Abstract: Datasets are often contaminated by various noises in many practical applications. The classical extreme learning machine (ELM) shows poor prediction accuracy and large fluctuation of prediction results in dealing with such datasets. To overcome this drawback, an exponential Laplace loss function was...
Abstract: In the era of big data and artificial intelligence, it is a common challenge for applied mathematics, statistics and computer science to extract valuable information and knowledge from complex data and models. Generative models are a class of powerful models which can potentially handle the above di...
Abstract: The general decay synchronization (GDS) of a class of recurrent neural networks (RNNs) with general activation functions and distributed delays was studied. By means of suitable LyapunovKrasovskii functionals and useful inequality techniques, some sufficient conditions for the GDS of considered RNN...
Abstract: A quasi-ARX multilayer learning network prediction model was established and applied to the adaptive control of nonlinear systems. The kernel of the model is an improved neuro-fuzzy network: one part is a 3-layer nonlinear network with an off-line training self-associative network, the other part is...
Abstract: The Mittag-Leffler stability of a class of discrete-time fractional-order neural networks was studied. Based on the discrete fractional calculus theory and the neural network theory, a class of discrete-time fractional-order neural networks were proposed. By means of the inequality techniques and th...
Abstract: The source code similarity refers to the functional similarity of different code segments, which touches off important research in the field of software engineering. The existing methods mainly extracted texts and structure features manually from source codes to calculate the similarity based on the...
Abstract: The state estimation of complex-valued neural networks with leakage delay and both discrete and distributed additive time-varying delays was studied. In the case where the activation function of the network was not required to be separated, through construction of the appropriate Lyapunov-Krasovskii...
Abstract: The evolutionary game was introduced to reduce errors caused by the non-line-of-sight environment in 3D TOA-geolocation problems. A general dynamic replication model was established for the 3D TOA-geolocation problem in the non-line-of-sight environment. With each measuring base station as a player ...
Abstract: The compressed sensing (CS) is a new signal sampling technology, which can reconstruct signals at sampling points far smaller than those in the traditional Nyquist sampling theorem for sparse signals. For the compressed sensing, a dynamic continuous system was used to study the sparse signal reconst...
Abstract: The leader-follower consensus of linear multi-agent systems was investigated. An event-triggered adaptive dynamic programming method was proposed based on the undirected graph formed by means of the communication topology among agents, and the approximate optimal control was designed with the approx...
Abstract: To efficiently predict the travel time on the expressway, the travel time was studied with the gated recurrent neural network through collection of the swiping data of vehicles at toll gates on the expressway. By means of the developed prediction computer program, the effects of the proposed method ...
Abstract: The problem of finite-time combination synchronization for a class of complex-variable chaotic systems was investigated. Firstly, for the synchronization mode in signal transmission, the multi-switching synchronization behavior among multiple chaotic systems was analyzed. Secondly, based on the pres...
