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http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3369Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Espejo-Meana, S. | - |
| dc.creator | Domínguez-Castro, R. | - |
| dc.creator | Carmona-Galán, R. | - |
| dc.creator | Rodríguez-Vázquez, Ángel | - |
| dc.date | 2008-03-30T18:54:30Z | - |
| dc.date | 2008-03-30T18:54:30Z | - |
| dc.date | 1994-09 | - |
| dc.date.accessioned | 2017-01-31T01:01:20Z | - |
| dc.date.available | 2017-01-31T01:01:20Z | - |
| dc.identifier | Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems (MICRONEURO’94), pp. 383-391, Turin, Italy, September 1994. | - |
| dc.identifier | http://hdl.handle.net/10261/3369 | - |
| dc.identifier.uri | http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3369 | - |
| dc.description | This paper presents a continuous-time Cellular Neural Network (CNN) chip [1] for the application of Connected Component Detection (CCDet) [2]. Projection direction can be selected among four different possibilities. Every cell (or pixel) in the 32 x 32 array includes a photosensor circuitry and an automatic tuning circuitry to adapt to average environmental illumination. Electrical image uploading is possible as well. Input pixel-values are stored on local memories (one per cell), allowing sequential processing of the acquired image in different directions. | - |
| dc.description | The prototype has been designed and fabricated on a standard digital CMOS technology: 1.6μm, n-well, single-poly, double-metal. Circuit implementation is based on current-mode techniques and uses a systematic approach valid for any CNN application [3]. Cell dimensions, including the CNN processing circuitry, the photosensor and the adaptive circuitry are 145 x 150 μm2, of which the sensor and adaptive circuitry amounts to ~15% of the total pixel area and the wiring and multiplexing (required for direction selectability) to about 40%. The remaining 45% corresponds to the CNN processing circuitry. Pixel density is ~46 cells/mm2, and power dissipation is 0.33mW/cell. These area and power figures forecast single-die CMOS chips with 100 x 100 complexity and about 3W power consumption. | - |
| dc.description | Peer reviewed | - |
| dc.format | 172669 bytes | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Institute of Electrical and Electronics Engineers | - |
| dc.rights | openAccess | - |
| dc.title | A countinuous-time cellular neural network chip for direction-selectable connected component detection with optical image acquisition | - |
| dc.type | Comunicación de congreso | - |
| Appears in Collections: | Digital Csic | |
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