A learning-by-example method for improving performance of network topologies
β Scribed by Samuel Pierre
- Publisher
- Elsevier Science
- Year
- 1994
- Tongue
- English
- Weight
- 932 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0952-1976
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Networks that solve specific visual tasks, such as the evaluation of spatial relations with hyperacuity precision, can be easily synthesized from a small set of examples. The present paper describes a series of simulated psychophysical experiments that replicate human performance in hyperacuity task
In backpropagation networks, unlearned regions are left between categories if the learning samples are comparatively small. Such unlearned regions are one of the reasons for the degradation of network generalization ability. To improve the generalization ability, it is preferable that the boundaries
## Abstract The MR signal is sensitive to diffusion. This effect can be increased by the use of large, balanced bipolar gradients. The gradient systems of MR scanners are calibrated at installation and during regular servicing visits. Because the measured apparent diffusion constant (ADC) depends o
## Abstract A method for improving broadband phase performance of commonβsource/commonβgate (CS/CG) active balun is presented. By setting different terminal impedances and DC bias, the phase error of the balun can be controlled within 7Β° from 1 to 20 GHz in simulation. A fabricated 2β40 GHz balance