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From neural-based object recognition toward microelectronic eyes
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Bang, Sa Hyun Sheu, Bing J. |
| Copyright Year | 1994 |
| Description | Engineering neural network systems are best known for their abilities to adapt to the changing characteristics of the surrounding environment by adjusting system parameter values during the learning process. Rapid advances in analog current-mode design techniques have made possible the implementation of major neural network functions in custom VLSI chips. An electrically programmable analog synapse cell with large dynamic range can be realized in a compact silicon area. New designs of the synapse cells, neurons, and analog processor are presented. A synapse cell based on Gilbert multiplier structure can perform the linear multiplication for back-propagation networks. A double differential-pair synapse cell can perform the Gaussian function for radial-basis network. The synapse cells can be biased in the strong inversion region for high-speed operation or biased in the subthreshold region for low-power operation. The voltage gain of the sigmoid-function neurons is externally adjustable which greatly facilitates the search of optimal solutions in certain networks. Various building blocks can be intelligently connected to form useful industrial applications. Efficient data communication is a key system-level design issue for large-scale networks. We also present analog neural processors based on perceptron architecture and Hopfield network for communication applications. Biologically inspired neural networks have played an important role towards the creation of powerful intelligent machines. Accuracy, limitations, and prospects of analog current-mode design of the biologically inspired vision processing chips and cellular neural network chips are key design issues. |
| File Size | 622132 |
| Page Count | 10 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19950018837 |
| Archival Resource Key | ark:/13960/t0ht7jt55 |
| Language | English |
| Publisher Date | 1994-05-11 |
| Access Restriction | Open |
| Subject Keyword | Cybernetics Computer Vision Multipliers Microprocessors Neural Nets Electric Networks Data Transmission Very Large Scale Integration Massively Parallel Processors Chips Electronics Pattern Recognition Synapses Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
