Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
- We introduce a transformation, named rephasing, that manipulates the timing parameters in control-dataflow graphs. Traditionally high-level synthesis systems for DSP have either ...
This paper presents a hardware-based dynamic optimizer that continuously optimizes an application’s instruction stream. In continuous optimization, dataflow optimizations are p...
Brian Fahs, Todd M. Rafacz, Sanjay J. Patel, Steve...
– This paper addresses the problem of resource allocation in a multiservice optical network based on an Overlapped-CDMA system. A joint transmission power and overlapping coeffic...
Robert Raad, Elie Inaty, Paul Fortier, Hossam M. H...
Constrained continuous optimization is still an interesting field of research. Many heuristics have been proposed in the last decade. Most of them are based on penalty functions....