MODA: moving object detecting architecture
A type of cellular neural network (CNN) is described, which may be classified in the broader category of generalized cellular neural networks (GCNNs). Its novelty consists both in the task it performs and in its architecture and way of operation. The input to the network is a two-dimensional picture...
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| Veröffentlicht in: | IEEE transactions on circuits and systems. 2, Analog and digital signal processing Analog and digital signal processing, 1993-03, Vol.40 (3), p.174-183 |
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| container_end_page | 183 |
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| container_issue | 3 |
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| container_title | IEEE transactions on circuits and systems. 2, Analog and digital signal processing |
| container_volume | 40 |
| creator | Cimagalli, V. Bobbi, M. Balsi, M. |
| description | A type of cellular neural network (CNN) is described, which may be classified in the broader category of generalized cellular neural networks (GCNNs). Its novelty consists both in the task it performs and in its architecture and way of operation. The input to the network is a two-dimensional picture that is processed continuously in order to detect real time trajectories of moving objects in a noisy environment. MODA is designed by synthesis, so that it does not require learning, and it performs its task by implementing a nonlinear continuous functional in a vector space. The network, its architecture, its equations, and the method of design are described. In addition, the new network is compared with known paradigms of ANN and CNN. Results of simulations are also reported.< > |
| doi_str_mv | 10.1109/82.222816 |
| format | Article |
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| identifier | ISSN: 1057-7130 |
| ispartof | IEEE transactions on circuits and systems. 2, Analog and digital signal processing, 1993-03, Vol.40 (3), p.174-183 |
| issn | 1057-7130 1558-125X |
| language | eng |
| recordid | cdi_pascalfrancis_primary_4851296 |
| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Cellular neural networks Design methodology Electric, optical and optoelectronic circuits Electronics Exact sciences and technology High performance computing Network synthesis Neural networks Noise shaping Nonlinear equations Object detection Sensor arrays Shape Working environment noise |
| title | MODA: moving object detecting architecture |
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