In computer science and machine learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference that communication is allowed between neighbouring units only. Typical applications include image processing, analyzing 3D surfaces, solving partial differential equations, reducing non-visual problems to geometric maps, modelling biological vision and other sensory-motor organs.[1]
CNN is not to be confused with convolutional neural networks (also colloquially called CNN).
^Slavova, A. (2003-03-31). Cellular Neural Networks: Dynamics and Modelling. Springer Science & Business Media. ISBN 978-1-4020-1192-4.
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learning, cellularneuralnetworks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neuralnetworks, with the difference...
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proliferation of neural progenitors. Growth factors comprise the second major set of candidates of epigenetic regulators of cellular differentiation....
intelligence that uses evolutionary algorithms to generate artificial neuralnetworks (ANN), parameters, and rules. It is most commonly applied in artificial...
represented as a convolutional neuralnetwork, and trained neuralnetworks to reproduce existing cellular automata In this light, cellular automata may be seen...
Ph.D. – Contributor to both the nonlinear circuit theory and cellularneuralnetwork theory, and professor of electrical engineering and computer science...
are capable of receiving and relaying voice, data, and TV signals. Cellularnetworks use several radio communications technologies. The systems divide...
such as the neuralnetworks found in brains. He published his first paper in Reviews of Modern Physics investigating elementary cellular automata (Rule...
Neural decoding is a neuroscience field concerned with the hypothetical reconstruction of sensory and other stimuli from information that has already been...
scalability and parallelization. Alife and cellular automata share a closely tied history. Artificial neuralnetworks are sometimes used to model the brain...
and dynamic interactions between genes, on the cellular level (CNGM can also be used to model neural systems as well). Systems neuroscience research...
Evolving Asynchronous and Scalable Non-Uniform Cellular Automata. Proc. of Intl. Conf. on Artificial NeuralNetworks and Genetic Algorithms (ICANNGA97), Springer-Verlag...
tissue and neural structures of the nervous system. Immunostaining Category: Neuroanatomy Neuropharmacology is the study of how drugs affect cellular function...
together to form neural pathways, neural circuits, and larger brain networks. At this level of analysis, neuroscientists study how different neural circuits analyze...
The field of neural development draws on both neuroscience and developmental biology to describe and provide insight into the cellular and molecular...
entitled “Physics of Computation”; Hopfield teaching about his work in neuralnetworks and Mead about his work in the area of replicating neuronal structures...
Neuroplasticity, also known as neural plasticity or brain plasticity, is the ability of neuralnetworks in the brain to change through growth and reorganization...
modulated. The connections between neurons can form neural pathways, neural circuits, and larger networks that generate an organism's perception of the world...
established "classical" nature-inspired models of computation are cellular automata, neural computation, and evolutionary computation. More recent computational...
replace, or enhance neural systems. Neural engineers are uniquely qualified to solve design problems at the interface of living neural tissue and non-living...
Csikszentmihalyi founder of Flow- theory. Tamás Roska is co-inventor of CNN (cellularneuralnetwork). Some internationally well-known figures of today include: mathematician...
closer to a higher order recurrent neuralnetwork. The same model has also been used to mimic the evolution of cellular differentiation and even multicellular...
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