Complex Valued Neural Networks
Periodic solutions for complex valued neural networks of neutral type by combining graph theory with coincidence degree theory
... By combining graph theory with coincidence degree theory as well as Lyapunov functional method, by constructing the same Lyapunov functionals in the proofs of the existence of periodic solutions and global exponential ...
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Robust stability analysis of impulsive complex valued neural networks with mixed time delays and parameter uncertainties
... of complex-valued neural networks (CVNNs) is that they can directly deal with the two-dimensional data, which can also be processed by RVNNs but needs double ...the complex signals are ...
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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 ...
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Stability and Hopf bifurcation analysis of fractional order complex valued neural networks with time delays
... of neural networks, since the importance of the memory term is extremely high, the incorporation of fractional terms into neural networks leads to a new class of networks called ...
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State estimation for complex valued memristive neural networks with time varying delays
... the 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, ...
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Dissipativity analysis and stabilization for discontinuous delayed complex valued networks via matrix measure method
... construct complex-valued set-valued maps and give the basic framework of complex-valued differential ...discontinuous complex-valued neural networks by using ...
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Pseudo almost periodic solutions for quaternion valued cellular neural networks with discrete and distributed delays
... quaternion-valued neural networks (QVNNs), as an extension of the complex-valued neural networks (CVNNs), can deal with multi-level information and re- quire only half the ...
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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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Learning Dynamics of the Complex Valued Neural Network in the Neighborhood of Singular Points
... Complex-valued neural networks have been applied in various fields dealing with complex numbers or two- dimensional data such as signal processing and image processing ...The ...
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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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Complex Valued Recurrent Neural Network: From Architecture to Training
... with complex parameters to the complex valued recurrent neural network of a special ...the complex valued ...plex-valued neural networks. A lot of research ...
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Robust stability analysis of quaternion valued neural networks via LMI approach
... decades, neural networks (NNs) have been ap- plied in various areas throughout science and engineering, such as signal processing, im- age processing, pattern recognition, associative memory and ...
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Remarks on Direct System Identification Using Hypercomplex–Valued Neural Network with Application to Time–Series Estimation
... for neural networks has attracted increasing attention from engineering re- search fields because it helps to learn to handle a wide variety of geometric objects and their transformation in the form of ...
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Combined Complex-Valued Artificial Neural Network (CCVANN)
... single, neural network ...for neural network models (SNN) that consist of a combination of the candidate neural ...combining neural network models in ...
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A Modfied Real-Valued Feed-Forward Neural Network Low-Pass Equivalent Behavioral Model for RF Power Amplfiers
... Abstract—This work addresses the low-pass equivalent behavioral modeling of radio frequency (RF) power amplifiers (PAs) for modern wireless communication systems. Similar to a previous approach, here the PA behavioral ...
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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, color ...
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Concurrent blind channel equalization with phase transmittance RBF neural networks
... In this section we evaluate the PTRBFNN performance in comparison with the classical complex valued RBFNN whose basis function is given by (1). We adopt a 16-QAM digital modulation with a unit variance ...
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Data Mining using Neural Networks
... Many cryptographers would agree that, it is only because of the concept of semaphore‘s design invention that, the exploration of Internet QoS might have came into existence. The notion that cyberneticists collaborate ...
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Neural Based Routing Method for Alleviating Congestion in Complex Networks
... Understanding the dynamics of packet transmission on networks is also an important task in analyzing the onset of traffic congestion. From this viewpoint, Ohira et al. [17] illustrated the onset of phase ...
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Networks in cognitive science
... world networks, on the other hand, turn out to be optimal in the sense that finite connectivity allows the individuals to use a finite amount of memory, as in lattices, while the small-‐world property prevents ...
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