Hopfield-neural-net
Bifurcation Analysis for a Two Dimensional Discrete Time Hopfield Neural Network with Delays
... as neural oscillators,” in Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks (IWANN ’03), ...discrete-time Hopfield neural networks,” ...
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Super Resolution Land Cover Pattern Prediction Using a Hopfield Neural Network
... a Hopfield neural network technique to super-resolution mapping of land cover features larger than a pixel, using information of pixel composition determined from soft classification, and now show how our ...
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A method of gene diagnosis based on Hopfield neural network
... discrete Hopfield neural networks not only has an important theoretical significance, but also is the foundation of the applications of the ...a neural network complete the tasks by the process of ...
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Superresolution mapping using a hopfield neural network with fused images
... [12], Hopfield neural net- work (HNN) optimization [13]–[17], two-point histrogram op- timization [18], genetic algorithms [19], and feedforward neural networks ...
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Hyperspectral Image Change Detection Using Hopfield Neural Network
... The Change detection refers to recognizing dissimilarities arising in the characteristics of an object, over a period of time. Widespread application of change detection in hyper spectral images in areas like remote ...
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Printed Gujarati Script OCR using Hopfield Neural Network
... artificial neural network ...classification Neural network and SVM are used in the paper [5]. Back propagation neural network with Gradient descent with momentum & adaptive learning rate is used ...
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Recognition of Isolated Handwritten Oriya Numerals using Hopfield Neural Network
... Designing an automatic pattern recognition system is a challenging task. However, despite the design challenges, its enormous application potentials have attracted the attention of researchers and developers over the ...
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Competitive Hopfield Neural Network Model for Evaluating Pedicle Screw Placement Accuracy
... In this paper, the application of an X-ray image segmentation algorithm based on a Competitive Hopfield Neural Network (CHNN) model for evaluating the insertion accuracy of pedicle scre[r] ...
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A New OFDMA Scheduler for Delay Sensitive Traffic Based on Hopfield Neural Networks
... This paper introduces a novel joint channel and queuing-aware OFDMA scheduler for delay-sensitive traffic based on a hopfield neural network (HNN) scheme. It allows providing an optimum OFDMA performance by ...
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Hopfield Neural Networks for Aircrafts’ Enroute Sectoring: KRISHAN-HOPES
... research. Hopfield neural networks or simply Hopfield nets, a widely used popular category of feedback neural network or recurrent neural networks may play a very important role in ...
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Study Of Hopfield Neural Network For Fingerprint Verification Based On Fast Fourier Transform
... of Hopfield net is the synaptic weights that referred to ...for Hopfield neural network to determine the weight matrix and there were a number of learning rules have been suggested since then ...
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A low complexity Hopfield neural network turbo equalizer
... Hopfield neural network (HNN) can be used to jointly equalize and decode information transmitted over a highly dispersive Rayleigh fading multipath ...Hopfield neural network turbo equalizer (HNN-TE) is ...
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IMPORTANCE AND USES OF HOPFIELD NEURAL NETWORK AND PATTERN STORAGE
... of neural networks by genetic algorithms and messy genetic algorithms”, in Proceedings of 2nd IASTED ...and Neural Networks, ...multi-layered neural networks that ...
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Open quantum generalisation of Hopfield neural networks
... In order to make our ideas concrete we introduce a generalisation based on OQSs of one of the most studied NN systems, the Hopfield model [22] (see Fig. 1). The dissipative part of the dynamics corresponds to the ...
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Existence and Stability of Periodic Solution in Impulsive Hopfield Networks with Time-Varying Delays
... systems, neural networks such as Hopfield neural networks, bidirectional neural networks and recurrent neural networks often are subject to ...
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Stability Criteria Of Fully Connected Hopfield Artificial Neural Network
... interconnected Hopfield Artificial Neural Network (HANN). Hopfield Neural Network is a multiple loop feedback neural network which can be used as an associative ...
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PERFORMANCE ANALYSIS OF HOPFIELD MODEL OF NEURAL NETWORK WITH EVOLUTIONARY APPROACH FOR PATTERN RECALLING
... The simulation results (i.e. tables 4-7) are indicating that genetic algorithm has more success rate then the Hebbian rule for recalling the taken set of objects, which are containing 0, 1, 2, and 3 bit errors from ...
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Multiresolution neural networks for image edge detection and restoration
... In chapter 4, an edge detection scheme was detailed, based on the multiresolution model outlined in chapter 2 and was implemented using the proposed hierarchical Hopfield neural network.[r] ...
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Pseudo random number generator based on Neuro Fuzzy models
... Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield ...
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Tolerance of Pattern Storage Network for Storage and Recalling of Compressed Image using SOM
... The network’s ability to correct noisy patterns is also extremely limited and deteriorates with packing density of the network. New patterns could hardly be associated to the stored patterns. Since Hebbian rule had the ...
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