搜索资源列表
m4-heuristics
- Best-first search Greedy best-first search A* search Heuristics Local search algorithms Hill-climbing search Simulated annealing search Local beam search Genetic algorithms
ders4_2007
- Develop two different implementations of Snake model by using a Greedy algorthm and an Gradient Descent method. Compare results. Put all details and results in your report.
ders5_2007
- Develop two different implementations of Snake model by using a Greedy algorthm and an Gradient Descent method. Compare results. Put all details and results in your report.
ders6_2007
- Develop two different implementations of Snake model by using a Greedy algorthm and an Gradient Descent method. Compare results. Put all details and results in your report.
ders7_2006
- Develop two different implementations of Snake model by using a Greedy algorthm and an Gradient Descent method. Compare results. Put all details and results in your report.
ders8_2006
- Develop two different implementations of Snake model by using a Greedy algorthm and an Gradient Descent method. Compare results. Put all details and results in your report.
Greedy-Hop-Distance-Routing-using-Tree-Recovery-o
- Sensor routing techniques
infocom11-cheng
- In this paper, we propose a novel compressive sensing (CS) based approach for sparse target counting and positioning in wireless sensor networks. While this is not the first work on applying CS to count and localize targets, it is the first t