Testing the Hopfield neural network example class
A low complexity Hopfield neural network turbo equalizer
... The HNN has also been shown by several authors to be able to decode balanced check codes [17,18]. These codes, together with methods for encoding and decoding, were first proposed in [19], but it was later shown in ...
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THE HOPFIELD NEURAL NETWORK IN THE ASPECT OF THE STABILIZATION OF THE DISPLACEMENT PHENOMENON
... control network set on buildings located on expansive soils is particularly vulnerable to load changes, which cause changes in the direction of the trajectory of the movement of ...typical example is point ...
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Incorporating web analysis into neural networks: An example in hopfield net searching
... net, neural network, spreading activa- tion, Web analysis, Web ...RTIFICIAL neural network learning algorithms have been applied in many different applications such as classifica- tion, ...
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Superresolution mapping using a hopfield neural network with fused images
... In comparison with the hard classification and the traditional HNN superresolution mapping, the resulting land cover map produced by the HNN using the fused image is visually more accurate. Similar to the simulated ...
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Printed Gujarati Script OCR using Hopfield Neural Network
... For testing, characters which are segmented from the scanned document by preprocessing are ...The Hopfield neural network with 900 input neurons and 900 output neurons are used for ...
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Improvements to the Hopfield Neural Network Solution of the TWT Scheduling Problem
... specific example studied here, we consider the risk calculations associated with nearly 100 dif- ferent portfolios, yielding altogether 556 jobs of an average size of 792 seconds to be ...
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Super Resolution Land Cover Pattern Prediction Using a Hopfield Neural Network
... the testing of the technique, the various weighting parameters, k 1 to k 8 remained at the same values, and the maintenance of successful results for each spatial arrangement indicates the ability of the approach ...
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Study Of Hopfield Neural Network For Fingerprint Verification Based On Fast Fourier Transform
... Of Hopfield Neural Network For Fingerprint Verification Based On Fast Fourier Transform Ramesh Chandra Sahoo, Sateesh Kumar Pradhan, Somesh Kumar Abstract: In this paper we are analyzing storing ...
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Competitive Hopfield Neural Network Model for Evaluating Pedicle Screw Placement Accuracy
... 2. Define the energy function whose minimization will lead to an optimum solution to the problem. The problem of segmenting an image of n×n pixels into k classes is to choose a suitable architecture for the HNN. For this ...
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Automatic brain tumor medical image classification using hyperbolic Hopfield neural network
... Hyperbolic Hopfield Neural ...hyperbolic Hopfield neural network is used where it contains two phases such as training and ...hyperbolic Hopfield neural network, ...
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Class-switching neural network ensembles
... [11,25,3,4,27,22,2,9,26,6], neural networks [14,31,23,28,22,26,8], support vector machines [17,29,30], ...For example, in randomization [18], the base learners are decision trees generated with a modified ...
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STUDY ON ENERGY ANALYSIS OF HOPFIELD NETWORK
... 1) data acquisition and preprocessing, 2) data representation, and 3) decision making. The problem domain dictates the choice of sensor(s), preprocessing technique, representation scheme, and the decision making model. ...
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Appling a Novel Cost Function to Hopfield Neural Network for Defects Boundaries Detection of Wood Image
... nondestructive testing is an effective method for accessing to internal information of ...nondestructive testing, such as appearance judgment, acoustic emission testing, ultrasonic testing, ...
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Super resolution target identification from remotely sensed images using a Hopfield neural network
... a Hopfield Neural Network Andrew ...the class composition of image pixels, but their output provides no indication of how these classes are distributed spatially within the instantaneous field ...
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Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach.
... and Network Architecture At this stage, once the Wishart classifier has performed an initial classification, all the pixels have been classified into eight clusters or ...
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Pattern Recognition Neural Network and Class of Grades
... of neural network to recognise pattern by using pattern recognition neural network tool box to predict the class of Science laboratory technology students in Federal polytechnic ...
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Hybrid imperialistic competitive algorithm incorporated with hopfield neural network for robust 3 satisfiability logic programming
... the testing phases as it was absolutely free from errors in the training ...a Hopfield Neural Network, and it is closest to achieving the global minima, regardless of the number of number of ...
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Chaotic Behavior of a Class of Neural Network with Discrete Delays
... delayed neural network models considering neuron gain (the maximum slope of the sig- moidal activation function) as ...in Hopfield mo- del and showed that symmetrically connected continu- ous time ...
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Predicting Testing Effort Using Artificial Neural Network
... and testing effort measured in terms of number of lines changed or added per ...estimate testing effort within 35 percent of the actual effort in more than ...
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Optimizing hopfield neural network for super-resolution mapping
... Keywords: Euler; optimization; ordinary differential equation; remote sensing; super-resolution mapping ABSTRAK Penderiaan jauh merupakan suatu sumber maklumat berkenaan tentang litupan tanah di atas permukaan bumi. ...
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