Results 281 to 290 of about 683,409 (316)
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IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 1993
A concise tutorial description of the cellular neural network (CNN) paradigm is given, along with a precise taxonomy. The CNN is defined, and the canonical equations are described. The importance of many independent input signal arrays, adaptive templates, and the multilayer capability is emphasized and motivated by examples.
Chua, Leon O., Roska, Tamás
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A concise tutorial description of the cellular neural network (CNN) paradigm is given, along with a precise taxonomy. The CNN is defined, and the canonical equations are described. The importance of many independent input signal arrays, adaptive templates, and the multilayer capability is emphasized and motivated by examples.
Chua, Leon O., Roska, Tamás
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International Journal of Bifurcation and Chaos, 2003
A systematic design methodology for finding CNN parameters with prescribed functions is proposed. A given function (task) is translated into several local operations, and they are realized as stable states of the CNN system. Many CNN parameters (CNN genes) with the same functions can be easily derived by using this design methodology.
Itoh, Makoto, Chua, Leon O.
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A systematic design methodology for finding CNN parameters with prescribed functions is proposed. A given function (task) is translated into several local operations, and they are realized as stable states of the CNN system. Many CNN parameters (CNN genes) with the same functions can be easily derived by using this design methodology.
Itoh, Makoto, Chua, Leon O.
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International Journal of Bifurcation and Chaos, 2004
In this paper, we propose a multipurpose hysteresis CNN (cellular neural network) made of first-order cells with hysteresis switches. The hysteresis CNN has applications not only in image processing, but also in pattern formation, nonlinear wave propagation and associative and dynamic memories, because each hysteresis CNN cell has two operating modes,
Itoh, Makoto, Chua, Leon O.
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In this paper, we propose a multipurpose hysteresis CNN (cellular neural network) made of first-order cells with hysteresis switches. The hysteresis CNN has applications not only in image processing, but also in pattern formation, nonlinear wave propagation and associative and dynamic memories, because each hysteresis CNN cell has two operating modes,
Itoh, Makoto, Chua, Leon O.
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International Journal of Embedded and Real-Time Communication Systems, 2021
The paper is dedicated to distributed convolutional neural networks on a resource constrained devices cluster. The authors focus on requirements that meet the users' needs. Based on this, architecture of the system is proposed. Two use cases of CNN computations on a ROCK-CNN cluster are mentioned, and algorithms for organizing distributed convolutional
Rezeda Khaydarova +5 more
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The paper is dedicated to distributed convolutional neural networks on a resource constrained devices cluster. The authors focus on requirements that meet the users' needs. Based on this, architecture of the system is proposed. Two use cases of CNN computations on a ROCK-CNN cluster are mentioned, and algorithms for organizing distributed convolutional
Rezeda Khaydarova +5 more
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International Journal of Bifurcation and Chaos, 1999
A cellular neural/nonlinear network (CNN) [Chua, 1998] is a biologically inspired system where computation emerges from a collection of simple nonlinear locally coupled cells. This paper reviews our recent research results beginning from the standard uncoupled CNN cell which can realize only linearly separable local Boolean functions, to a generalized
Dogaru, Radu, Chua, Leon O.
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A cellular neural/nonlinear network (CNN) [Chua, 1998] is a biologically inspired system where computation emerges from a collection of simple nonlinear locally coupled cells. This paper reviews our recent research results beginning from the standard uncoupled CNN cell which can realize only linearly separable local Boolean functions, to a generalized
Dogaru, Radu, Chua, Leon O.
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International Journal of Software Science and Computational Intelligence, 2022
Emotion is a feeling that can be expressed by different mediums. Emotion analysis is a key task in NLP which is responsible for judging the emotional tendency of texts. Currently, in a complex multi-semantic environment, it still suffers from poor performance.
Zhiwei Zhan +6 more
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Emotion is a feeling that can be expressed by different mediums. Emotion analysis is a key task in NLP which is responsible for judging the emotional tendency of texts. Currently, in a complex multi-semantic environment, it still suffers from poor performance.
Zhiwei Zhan +6 more
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G-CNN and F-CNN: Two CNN based architectures for face recognition
2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), 2017In the recent past, deployment of Convolutional Neural Networks (CNN) has led to prodigious success in many pattern recognition tasks. This is mainly due to the very nature of CNN, that is its ability to work in a similar manner to that of the visual system of the human brain.
A Vinay +7 more
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Nonlinear CNN: improving CNNs with quadratic convolutions
Neural Computing and Applications, 2019In this work, instead of designing deeper convolutional neural networks, we investigate the relationship between the nonlinearity of convolution layer and the performance of the network. We modify the normal convolution layer by inserting quadratic convolution units which can map linear features to a higher-dimensional space in a single layer so as to ...
Yiyang Jiang +4 more
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CNN-SkelPose: a CNN-based skeleton estimation algorithm for clinical applications
Journal of Ambient Intelligence and Humanized Computing, 2019Computer vision based patient activity monitoring systems can be attractive for various unobtrusive clinical applications. Such a monitoring system can be developed using movement information derived from the skeleton model of the current body pose, e.g. obtained using a depth camera.
Luis A. Zavala-Mondragon +3 more
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Proceedings of the 7th International Conference on Computational Systems-Biology and Bioinformatics, 2016
Unravelling gene expression has become a critical procedure in bioinformatics world today and required continuous efforts to form a complete picture of enhancers. Enhancers are explicit patterns of gene expression that bound by activators to stimulate transcription.
Yu, Shiong Wong +2 more
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Unravelling gene expression has become a critical procedure in bioinformatics world today and required continuous efforts to form a complete picture of enhancers. Enhancers are explicit patterns of gene expression that bound by activators to stimulate transcription.
Yu, Shiong Wong +2 more
openaire +1 more source