real-valued neural networks
State estimation for complex valued memristive neural networks with time varying delays
... complex-valued neural net- works model has undergone a research upsurge, due to the more extensive applications, including radar imaging, electromagnetic waves, remote sensing, quantum devices, and so on ...
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Parameter range dependent robust stability conditions for quaternion valued neural networks with time delays
... Since neural networks had been proposed in the 1940s, they have been widely studied by many researchers, due to the many applications in various areas, such as associative memory, optimization, pattern ...
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Pseudo almost periodic solutions for quaternion valued cellular neural networks with discrete and distributed delays
... of real-valued neural networks (RVNNs) has been studied by many authors [13–15, ...the neural network model with time ...cellular neural networks (QVCNNs) with discrete ...
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LMI conditions for some dynamical behaviors of fractional order quaternion valued neural networks
... quaternion-valued neural networks (QVNNs), as a universal promotion of real-valued neural networks (RVNNs) and complex-valued neural networks (CVNNs), ...
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Robust stability analysis of impulsive complex valued neural networks with time delays and parameter uncertainties
... of neural networks, complex signals are usually preferable [–], so it is necessary to analyze complex-valued neural networks (CVNNs), which deal with the complex-valued date, ...
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Periodic solutions for quaternion valued fuzzy cellular neural networks with time varying delays
... cellular neural networks (QVFCNNs) with time-varying delays are ...equivalent real-valued systems according to Hamilton’s multiplication ...
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Robust stability analysis of quaternion valued neural networks via LMI approach
... three real- or complex-valued neurons to ...quaternion- valued neuron is enough to represent one color via three channels ı, j and κ of QVNNs, which leads to a significant reduction in the dimension ...
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Combined Complex-Valued Artificial Neural Network (CCVANN)
... artificial neural networks (CVANN) whose parameters (weights, threshold values, inputs and outputs) are all complex numbers, will have applications in fields dealing with complex numbers such as ...
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Stability and Hopf bifurcation analysis of fractional order complex valued neural networks with time delays
... the real-valued NNs [, , –]. In real-valued NNs, continuously differentiable and bounded sigmoid activation functions are to be chosen, but in the case of a complex domain the activation ...
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Low-Pass Equivalent Behavioral Modeling of RF Power Amplifiers Using Two Independent Real-Valued Feed-Forward Neural Networks
... The simultaneous demands for linearity and efficiency can only be attained if a linearization scheme is integrated into the transmitter chain. Among the available strategies, digital baseband predistortion (DPD) is a ...
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Pseudo almost automorphic solutions of quaternion valued neural networks with infinitely distributed delays via a non decomposing method
... quaternion-valued neural network models have more advantages than the real-value neural network models in dealing with affine transformation in three- dimensional space, color image compression, ...
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Concurrent blind channel equalization with phase transmittance RBF neural networks
... be real valued, which inherently imposes some restrictions when the classical RBFNN is applied to blind channel equalization, since the forward transmittance does not explicitly convey any phase ...
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A Modfied Real-Valued Feed-Forward Neural Network Low-Pass Equivalent Behavioral Model for RF Power Amplfiers
... independent real-valued feed-forward artificial neural networks ...two real-valued ANNs are responsible for estimating the in-phase and quadrature components of a ...
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THE ROLE OF INFORMATION TECHNOLOGY ON THE GROWTH OF FIRMS: A VALUE ADDED ONSIDERATION
... Intervals [14]. Automatic web page classification algorithm extracted the features from the web pages, and each feature was discredited using standard algorithms. Then the features were ranked by using the measure of ...
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Evolutionary Algorithms For Neural Networks Binary And Real Data Classification
... Artificial Neural Networks (ANNs) are complicated networks emulating the way human rational neurons process ...the networks to give the right solution with the most optimized ...classify ...
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Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... a neural network? Figure 22 shows how a neural network can be embedded in the ...the neural network: the collision sensors to nodes in the collision layer, the proximity sensors to nodes in the ...
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An Introduction to Neural Networks - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... Neural networks are often used for statistical analysis and data modelling, in which their role is perceived as an alternative to standard nonlinear regression or cluster analysis techniques (Cheng & ...
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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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Quality Assessment and Prediction of Philippine Mangoes: A Convolutional Neural Network Approach
... specifically neural networks, is dynamically growing and one if its strengths is classification of images in real time using computer vision combined with machine learning in fruit quality ...
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For Real! XCS with Continuous Valued Inputs
... the real multiplexer ...the real multiplexer problem in more detail and Section 7 extends this discussion to hyper- rectangles, the decision surfaces constructed by interval ...the real multiplexer ...
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