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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2014/27359
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| Title: | (abstract) A High Throughput 3-D Inner Product Processor |
| Authors: | Daud, Tuan |
| Issue Date: | 7-Oct-1996 |
| Citation: | Minneapolis, MN |
| Abstract: | A particularily challenging image processing application is the real time scene acquisition and object discrimination. It requires spatio-temporal recognition of point and resolved objects at high speeds with parallel processing algorithms. Neural network paradigms provide fine grain parallism and, when implemented in hardware, offer orders of magnitude speed up. However, neural networks implemented on a VLSI chip are planer architectures capable of efficient processing of linear vector signals rather than 2-D images. Therefore, for processing of images, a 3-D stack of neural-net ICs receiving planar inputs and consuming minimal power are required. Details of the circuits with chip architectures will be described with need to develop ultralow-power electronics. Further, use of the architecture in a system for high-speed processing will be illustrated. |
| URI: | http://hdl.handle.net/2014/27359 |
| Appears in Collections: | JPL TRS 1992+
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