linear cellular neural networks
Doubly Periodic Traveling Waves in a Cellular Neural Network with Linear Reaction
... a linear function and hence our results can also be interpreted as existence criteria for solutions of a nontrivial linear problem depending on 6 ...
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Significant Location Detection & Prediction in Cellular Networks using Artificial Neural Networks
... autoregressive neural network design available in the MATLAB software, as it is suitable for predicting a time series using past values by using supervised ...a linear combination of squared errors and ...
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Image Noise Cancellation Using Linear Matrix Inequality and Cellular Neural Network
... Abstract—In this paper, the technique of image noise cancellation is presented by employing cellular neural networks (CNN) and linear matrix inequality (LMI). The main objective is to obtain ...
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Existence and Stability of Periodic Solution in Impulsive Hopfield Networks with Time-Varying Delays
... man-made neural systems, integration and communication delays are ubiquitous, and often become sources of instabil- ...electronic neural networks are usually time varying, and sometimes vary ...
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Matrix Measure Strategies for Stability of Cellular Neural Networks with Proportional Delays
... fuzzy cellular neural networks with time delay in the leakage term, discrete and unbounded distributed delays,” Math- ematical and Computer Modelling, ...arguments,” Neural Com- puting and ...
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Neural Networks A General Framework for Non Linear Function Approximation
... Motivated by the desire to obtain distributional results for the approximation that rely neither on large scale sample size nor on artificial data-generating assumptions, Section 6 shows how bootstrapping pairs ...
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Integro differential inequality and stability of BAM FCNNs with time delays in the leakage terms and distributed delays
... The paper is organized as follows. In Section 2, the new neural network model is for- mulated, and the necessary knowledge is provided. The existence and uniqueness of equilibrium point are presented in Section 3. ...
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Thyroid Segmentation and Volume Estimation Using CT Images
... In the experiments 10 CT images of patients are collected. Three slices of each patient is considered. After preprocessing thyroid non thyroid area are separated. Then initial segmentation using cellular automata ...
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An Evolutionary Approach: Analysis of Artificial Neural Networks
... Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process ...information. Neural networks, with their ...
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Solution of Linear Electrical Circuit Problem using Neural Networks
... Neural networks could be used to provide a general link from measurements or device simulations to circuit ...a neural network. The neural network then tries to learn the desired ...the ...
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Verification of Closed-loop Systems with Neural Network Controllers
... In this case study, we present a six-dimensional control-affine model of a quadrotor controlled by a feed-forward neural network initially introduced in [9], although here we have modified the controller to have ...
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Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... biological neural networks, the connection strengths are sometimes also called synaptic ...in linear algebra the term vector is often used in neural network ...vector. Neural ...
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Learning from data to predict future symptoms of oncology patients
... non- linear relationships by using an appropriate kernel function which maps the input data points onto a higher-dimensional feature space, transforming the non-linear relationships into linear ...
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THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION
... multilayer neural network with GA for selecting IDF and ontology based features gave 93% of accuracy, high precision and recall and lowest RMSE when comparing to all other ...
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New Distributed Data Fusion Using Pregel For Large Text Dataset
... In distributed database system, the database is shared on several computers. The computers in a distributed system communicate with one another through various communication media, such as high-speed networks or ...
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An Introduction to Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... The function of real neurons is extremely complex. However, the essential information processing attributes may be summarized as follows. A neuron receives input signals from many other (afferent) neurons. Each such ...
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Towards Linear Time Neural Machine Translation with Capsule Networks
... Time Neural Machine Translation Several papers have proposed to use neural net- works to directly learn the conditional distribution from a parallel corpus(Kalchbrenner and Blun- som, 2013; Sutskever et ...
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The decision optimization of product development by considering the customer demand saturation
... built linear and nonlinear relationships between customer demands and necessary resource requirements for production by using linear regression and neural networks, then forecasted the ...
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The Asymptotic Performance of Linear Echo State Neural Networks
... artificial neural network viewpoint, it shall be noticed that the internal noise regularizes the network in a way sharing interesting similarities with the well-known connection between noise at the network output ...
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Discriminating Similar Languages with Linear SVMs and Neural Networks
... The results we submitted to the shared task use a multi-class (one-vs-one) support vector machine (SVM) model with linear kernel. Although we experimented with various features, our final model included character ...
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