Outlining of boundaries of organs and tumors in CT and MRI images are prerequisite in medical applications. In this paper, a single layer Hopfield neural network called Contextual Hopfield Neural Network (CHNN) is presented for finding the edges of CT and MRI images. Different from the conventional 2-D Hopfield neural networks, the CHNN maps the two-dimensional Hopfield network at the original ...

Drawing important ideas from several sources, the idea of associative memory from psychology (Kohonen, 1977), the idea of Hebbian adaptation from neurophysiology (Hebb, 1949), the idea of neuron as a thresholding device from prior modeling work (McCulloch & Pitts, 1943) etc., Hopfield presented an elegant model of associative memory storage and retrieval in the brain (Hopfield, 1982; Hopfield, ...

Image restoration is a very important task in image processing. The Artificial Neural Network (ANN) approach was used to solve this problem, especially the Discrete Hopfield Network (DHN). This approach suffers from the fluctuation problem due to the use of the hard limit function as activation function. To overcome this shortcoming, we use in this work the Continuous Hopfield Network (CHN) tha...

In this paper, a new Hopfield-model net based on fuzzy possibilistic reasoning is proposed for the classification of multispectral images. The main purpose is to modify the Hopfield network embedded with fuzzy possibilistic -means (FPCM) method to construct a classification system named fuzzy-possibilistic Hopfield net (FPHN). The classification system is a paradigm for the implementation of fu...

We investigate the retrieval phase diagrams of an asynchronous fully-connected attractor network with non-monotonic transfer function by means of a mean-field approximation. We find for the noiseless zero-temperature case that this non-monotonic Hopfield network can store more patterns than a network with monotonic transfer function investigated by Amit et al. Properties of retrieval phase diag...

In this paper, we propose new sets of criteria for exponential robust stability of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. The L2−L∞ approach is applied to obtain new sets of stability criteria, under which T-S fuzzy Hopfield neural networks reduce the effect of external input to a prescribed level. These sets of criteria are presented based on the matrix norm and linear matrix ineq...

Password authentication using Hopfield Networks is presented in this paper .In this paper we discussed the Hopfield Network Scheme for Textual and graphical passwords, for which input Password will be converted in to probabilistic values. We observed how to get password authentication using Probabilistic values for Textual passwords and Graphical passwords. This study proposes the use of a Hopf...

Recently neural networks have been ploposed as new computational tools for solving constrained optimization problems. In this paper the minimum cost path fmding algorithm is proposed by using a Hopfield type neural network. In order to design a Hopfield type neural network, an energy function must be defmed at f i t . To achieve thii, the concept of a vector-represented network is used to descr...

The paper deals with a comparison between two different methods in generating sub-optimal solutions to the Hopfield-Tank TSP (traveling salesman problem) neural algorithm. Namely, the Hopfield-Tank TSP neural algorithm has been applied in the paper to the linear ship’s route, that is cycle voyage modeling, which means here finding the optimal visiting order of a given set of ports in such way a...

Abstract— In this paper the Hopfield neural networks are adopted to solve the quadratic assignment problem, which is a generalization of the traveling salesman’s problem (TSP), the graph-partitioning problem (GPP), and the matching problem. When the Hopfield neural network was applied alone, a sub-optimal solution was obtained. By adding the 2exchange we obtained a solution very close to the op...