reconfigurable neural net chip
Reconfigurable Neural Net Chip with 32K Connections
It contains 32,768 binary, programmable connections arranged in 256 'building block' neurons. Several'building blocks' can be connected to form long neurons with up to 1024 binary connections or to form neurons with analog connections. Single- or multi-layer networks can be imple(cid:173) mented with this chip. We have integrated this chip into a board system together with a digital signal processor and fast memory. This system is currently in use for image processing applications in which the chip extracts features such as edges and corners from binary and gray-level images.
Reconfigurable Neural Net Chip with 32K Connections
Graf, H. P., Janow, R., Henderson, D., Lee, R.
We describe a CMOS neural net chip with a reconfigurable network architecture. It contains 32,768 binary, programmable connections arranged in 256 'building block' neurons. Several'building blocks' can be connected to form long neurons with up to 1024 binary connections or to form neurons with analog connections. Single-or multi-layer networks can be implemented with this chip. We have integrated this chip into a board system together with a digital signal processor and fast memory.
Reconfigurable Neural Net Chip with 32K Connections
Graf, H. P., Janow, R., Henderson, D., Lee, R.
We describe a CMOS neural net chip with a reconfigurable network architecture. It contains 32,768 binary, programmable connections arranged in 256 'building block' neurons. Several'building blocks' can be connected to form long neurons with up to 1024 binary connections or to form neurons with analog connections. Single-or multi-layer networks can be implemented with this chip. We have integrated this chip into a board system together with a digital signal processor and fast memory.
Reconfigurable Neural Net Chip with 32K Connections
Graf, H. P., Janow, R., Henderson, D., Lee, R.
H.P. Graf, R. Janow, D. Henderson, and R. Lee AT&T Bell Laboratories, Room 4G320, Holmdel, NJ 07733 Abstract We describe a CMOS neural net chip with a reconfigurable network architecture. Itcontains 32,768 binary, programmable connections arranged in 256 'building block' neurons. Several'building blocks' can be connected to form long neurons with up to 1024 binary connections or to form neurons with analog connections. Single-or multi-layer networks can be implemented withthis chip. We have integrated this chip into a board system together with a digital signal processor and fast memory.