Hopfield Neural Network
Hybrid imperialistic competitive algorithm incorporated with hopfield neural network for robust 3 satisfiability logic programming
... From the results obtained, it can be deduced that HNN-3SATICA algorithm has outperformed HNN-3SATES algorithm and HNN-3SATGA. This can be observed when the ICA has the least computation time, the lowest SBC value and ...
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Super Resolution Land Cover Pattern Prediction Using a Hopfield Neural Network
... The results shown in Section 4 indicate that the Hopfield neural network technique described in this paper displays excellent potential for super-resolution land cover pattern prediction. Whereas the ...
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Printed Gujarati Script OCR using Hopfield Neural Network
... The Hopfield neural network with 900 input neurons and 900 output neurons are used for classification with training and testing pattern selected as ...
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Recognition of Isolated Handwritten Oriya Numerals using Hopfield Neural Network
... of Hopfield neural network (HNN) model in recognizing the handwritten Oriya (an Indian language) digits is ...the network in image form of 12×12. It is found that the network recognized ...
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Appling a Novel Cost Function to Hopfield Neural Network for Defects Boundaries Detection of Wood Image
... modified Hopfield neural network with a novel cost function was presented for detecting wood defects boundary in the ...of Hopfield neural ...
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Automatic brain tumor medical image classification using hyperbolic Hopfield neural network
... In this research, our proposed system introduces an effective framework Hyperbolic Hopfield neural network for CT brain image classification. Proposed Automatic brain tumor classification mechanism ...
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Competitive Hopfield Neural Network Model for Evaluating Pedicle Screw Placement Accuracy
... Competitive Hopfield Neural Network (CHNN) algorithm for performing X-ray image segmentation required for the automated assessment of the pedicle screw insertion ...
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Bifurcation Analysis for a Two Dimensional Discrete Time Hopfield Neural Network with Delays
... A bifurcation analysis is undertaken for a discrete-time Hopfield neural network with four delays. Conditions ensuring the asymptotic stability of the null solution are obtained with respect to two ...
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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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Modification of the mean-square error principle to double the convergence speed of a special case of Hopfield neural network used to segment pathological liver color images
... of Hopfield Neural Network (SCHNN) in segmenting cerebral images obtained using the Magnetic Resonance Imaging (MRI) ...technique. Hopfield network for the optimization applications ...
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A method of gene diagnosis based on Hopfield neural network
... of neural computation almost reduce to 0,and it requires a vector ...of Hopfield neural network limits the number of samples is less than the number of neurons, it also requires a huge number ...
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Super resolution target identification from remotely sensed images using a Hopfield neural network
... a Hopfield neural net- work formulated as an energy minimization ...the Hopfield neural network will be ...the Hopfield network to the problem of land cover target ...
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Optimizing hopfield neural network for super-resolution mapping
... Li, X., Du, Y., Ling, F., Feng, Q. & Fu, B., 2014. Superresolution mapping of remotely sensed image based on Hopfield neural network with anisotropic spatial dependence model. IEEE Geoscience and ...
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Superresolution mapping using a hopfield neural network with fused images
... Abstract—Superresolution mapping is a set of techniques to in- crease the spatial resolution of a land cover map obtained by soft- classification methods. In addition to the information from the land cover proportion ...
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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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Identification of Acceleration Harmonics for a Hydraulic Shaking Table by Using Hopfield Neural Network
... Adaptive signal processing technology has also been applied to identify harmonics. Ray and Sub- udhi [17] designed a nonlinear state estimation method by using ensemble Kalman ltering for estimating harmonics, ...
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Selective Harmonic Elimination PWM using Generalized Hopfield Neural Network for Multilevel Inverters
... Thus, to overcome these limitations, multilevel inverters The core rationale of using inverter is to fabricate a have been proposed for applications such as medium-voltage sinusoidal ac [r] ...
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A low complexity Hopfield neural network turbo equalizer
... In [16], the authors proposed a maximum likeli- hood sequence estimation (MLSE) equalizer which is able to equalize M-ary quadrature amplitude modulation (M-QAM) modulated signals in systems with extremely long memory. ...
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IMPORTANCE AND USES OF HOPFIELD NEURAL NETWORK AND PATTERN STORAGE
... the network is presented with an approximate pattern for recall, the activation dynamics may eventually lead to a stable state that may correspond to one of the spurious state or a false energy minimum, or to one ...
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Robust Artificial Immune System in the Hopfield network for Maximum k-Satisfiability
... of Hopfield neural network in logic programming has been successfully done by a few ...standalone Hopfield network has limitations especially in terms of complexity ...the ...
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