CMOS-based Stochastically Spiking Neural Network for Optimization under Uncertainties
University of Illinois at Chicago Chicago United States
Pagination or Media Count:
We present CMOS-based stochastically spiking neural network for optimization under uncertainties. We discuss a scenario generation circuit to non-parametrically estimateemulate statistics of uncertain costconstraints variables in an optimization problem. We also present a spiking neural network for linearquadratic programming. Scenario generation block stochastically controls spiking neural network to extract optimal solution of an optimization problem minimizing its expected cost.
- Solid State Physics