Architectural design and analysis of learnable self-feedback ratio-memory cellular nonlinear network (SRMCNN) for nanoelectronic systems.
In this paper, a learnable cellular nonlinear network (CNN) with space-variant templates, ratio memory (RM), and modified Hebbian learning algorithm is proposed and analyzed. By integrating both the modified Hebbian learning algorithm with the self-feedback function and a ratio memory into CNN archi...
| প্রকাশিত: | IEEE Transactions on VLSI systems 12, 11 (2004). |
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| প্রধান লেখক: | |
| বিন্যাস: | প্রবন্ধ |
| ভাষা: | English |
| বিষয়গুলি: |