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Denote x t x1 t , x2 t , . . . , xn t , xt x1t, x2t, . . . , xnt , xit s xi t s i 1, 2, . . . , n , s ∈ −τ, 0 , τ is a positive constant or τ ∞, the norm of a bounded continuous function space C −τ, 0 , R is defined as ‖φ‖ maxs∈ −τ,0 |φ s |, where |φ| max{|φi|, i 1, 2, . . . , n}, C −τ, 0 , R {φ ∈ C −τ, 0 , R : for all θ ∈ −τ, 0 , φ θ > 0}. We call an(More)
The performance of a proposed compact radial basis function was compared with the sigmoid basis function and the gaussian-radial basis function neural networks in 3D wireless sensor routing topology control, in underground mine rescue operation. Optimised errors among other parameters were examined in addition to scalability and time efficiency. To make the(More)
—We propose Sparse TSVM, a multi-class SVM classifier that determines k nonparallel planes by solving k related SVM-type problems. The Sparse TSVM promotes Twin SVM to one-versus-rest approach. And it capture classes' main feature better with the sparse algorithm. On several benchmark data sets, Sparse TSVM is not only fast, but shows good generalization.
This paper is concerned with analysis problem for the global exponential stability of recurrent neural networks (RNNs) with mixed discrete and distributed delays, unlike other papers, the nodes are associated with the topology of network. By using Lyapunov-Krasovskii functional and Young inequality, we give the sufficient condition of global exponential(More)
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