M Novey,T Adali
M Novey
In this paper, we use complex analytic functions to achieve independent component analysis (ICA) by maximization of non-Gaussianity and introduce the complex maximization of non-Gaussianity (CMN) algorithm. We derive both a gradient-descent...
D Masip,J Vitria
D Masip
In this paper, we propose a new supervised linear feature extraction technique for multiclass classification problems that is specially suited to the nearest neighbor classifier (NN). The problem of finding the optimal linear projection mat...
H Wang,S Chen,Z Hu et al.
H Wang et al.
Dimensionality reduction is usually involved in the domains of artificial intelligence and machine learning. Linear projection of features is of particular interest for dimensionality reduction since it is simple to calculate and analytical...
A one-layer recurrent neural network with a discontinuous hard-limiting activation function for quadratic programming [0.03%]
具有不连续硬限幅激活函数的一层递归神经网络在二次规划中的应用研究
Q Liu,J Wang
Q Liu
In this paper, a one-layer recurrent neural network with a discontinuous hard-limiting activation function is proposed for quadratic programming. This neural network is capable of solving a large class of quadratic programming problems. The...
Delay-dependent criteria for global robust periodicity of uncertain switched recurrent neural networks with time-varying delay [0.03%]
具时变延迟的不确定切换递归神经网络的全局鲁棒周期性判据
X Lou,B Cui
X Lou
In this paper, we introduce some ideas of switched systems into the field of neural networks and a large class of switched recurrent neural networks (SRNNs) with time-varying structured uncertainties and time-varying delay is investigated. ...
Cristian Filici
Cristian Filici
The object of this brief is to present and analyze the training of a single-layer neural network in order to solve ordinary differential equations (ODEs). Properties of the approximator are derived and some examples of its application are s...
Rubin Wang,Zhikang Zhang,Guanrong Chen
Rubin Wang
Based on the principle of energy coding, an energy function of a variety of electric potentials of a neural population in cerebral cortex is formulated. The energy function is used to describe the energy evolution of the neuronal population...
A new criterion of delay-dependent asymptotic stability for Hopfield neural networks with time delay [0.03%]
具有时滞的霍普菲尔德神经网络新的延迟相关渐近稳定性判据
Shaoshuai Mou,Huijun Gao,James Lam et al.
Shaoshuai Mou et al.
In this brief, the problem of global asymptotic stability for delayed Hopfield neural networks (HNNs) is investigated. A new criterion of asymptotic stability is derived by introducing a new kind of Lyapunov-Krasovskii functional and is for...
An improved algebraic criterion for global exponential stability of recurrent neural networks with time-varying delays [0.03%]
具有时变延迟的递归神经网络的全局指数稳定性的一种改进代数准则
Yi Shen,Jun Wang
Yi Shen
This brief paper presents an M-matrix-based algebraic criterion for the global exponential stability of a class of recurrent neural networks with decreasing time-varying delays. The criterion improves some previous criteria based on M-matri...
Ning Jin,Derong Liu
Ning Jin
In this letter, we develop the wavelet basis function neural networks (WBFNNs). It is analogous to radial basis function neural networks (RBFNNs) and to wavelet neural networks (WNNs). In WBFNNs, both the scaling function and the wavelet fu...