[PDF] Top 20 A Note on Hopfield Neural Network Stability

... The Hopfield neural network (HNN [1]–[3]) theory and its application are extensively discussed in literature, for example, [3]–[17], [19], [21]–[29] and the references cited ...problem on a ... See full document

... of Hopfield Neural Networks (HNN) has proved to be an efficient method for online parameter estimation in one-dimensional processes ...based on an extension of the 1D HNN introduced in [6] is ... See full document

... based on structure-activity relationships or screening of peptide libraries that contain many structural variants of the native ...novel neural network architecture for the improvement of metabolic ... See full document

... However, on most occasions, resolution of inverse problems involve poorly conditioned matrices, thus requiring robust and elaborate techniques like Singular Value Decomposition and artificial neural ... See full document

... transient stability assessment of electrical power system using Probabilistic Neural Network (PNN) and principle component ...Transient stability of a power system is first determined based ... See full document

... difficulties. Neural Networks have emerged as one important enabling technology in many scientific disciplines in solving previously unsolvable problems and in improving system ...performance. Stability is ... See full document

... adaptive neural network controller for a class of nonlinear ...RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are ...RBF ... See full document

... Hierarchical agglomerative clustering techniques start with as many clusters as there are unique values. Then pairs of cluster are successively merged till the optimal number of clusters is reached, depending on ... See full document

... the stability performance with reconstruction accuracy in terms of HIM and its components for the nine methods ...10). On this dataset, accuracy is independent of sample size, except for WGCNA and TOM which ... See full document

... exponential stability of an equilibrium ...of neural networks of Hopfield type, with time-varying coefficients and distributed ...exponential stability. The existence and global exponential ... See full document

... phenotypic stability of alfalfa genotypes based on the training of an artificial neural network considering the methodology of Eberhart and ...experiment on dry matter production of 92 ... See full document

... 7]), neural network models are nowadays a subject of active ...of neural network models is to establish conditions that assure the global stability of equilibrium states [15, 16, 17], ... See full document

... The extracted sentences are then passed on to the Word Isolation and Coding Module. This module separates the different words present in each sentence and codes them in the form of a matrix whose format is shown ... See full document

... of Hopfield neural networks (HNNs) for parameter ...is on time-invariant systems that are linear in the ...the network to the actual ... See full document

... A dynamical system is defined by a set of variables describing the state of the system and the laws for which the values of these variables change with respect to time. Variables can be regarded as discrete-time ... See full document

... book on Neurocomputing, Principles of Neurodynamics ...of neural network processing element called ADALINE, which was equipped with a powerful new learning law which, unlike the perceptron leaning ... See full document

... – Neural Networks offer the potential for providing a novel solution to the problem of data compression by its ability to generate an internal data ...This network, which is an application of back ... See full document

... based on a Likert type scale (created in 1932 by American educator and social psychologist Likert Rensis) is an instrument that features a cast of sentences for which the respondent expresses their degree of ... See full document

... n , and let d ( ) n be the desired complex value at the PTRBFNN output y ( ) n . In the context of channel equalization, d ( ) n is the original transmitted IQ symbol training sequence whose values are stored in a look ... See full document

... influences on the wind capacity because power is cubic proportional to wind speed in ...year on various ...speed on which the machine generates the rated wind generation, and cut-out speed that ... See full document