A Greedy Search Approach for Time-Interleaved ADCs Calibration Based on NRZ Input Patterns

Author(s):  
Yang Azevedo Tavares ◽  
Seunghyun Kim ◽  
Minjae Lee
Author(s):  
Marina G. Erechtchoukova ◽  
Stephen Y. Chen ◽  
Peter A. Khaiter

The evaluation of an organization’s environmental performance is an integral part of a corporate environmental management information system. This chapter considers an organization’s environmental impact assessment with respect to a water resource. It investigates formal approaches to the development of temporal monitoring designs for producing data sufficient to perform the assessment. In this study, simple random sampling, stratified random sampling, and designs obtained using greedy search have been investigated with respect to their compatibility with a corporate environmental management information system. All three approaches determine temporal monitoring designs with minimal costs and supply data sufficient for estimation of water quality indicators for a given level of uncertainty. It is shown that monitoring designs obtained using the greedy search approach will outperform other designs when the level of uncertainty in the estimate must be low. If high levels of uncertainty are tolerable, simple random designs become preferable due to their simplicity and effectiveness. The proposed approaches lead to automated procedures which can be easily integrated into a corporate environmental management information system.


2017 ◽  
Vol 5 (1) ◽  
pp. 45-69 ◽  
Author(s):  
JASON WYSE ◽  
NIAL FRIEL ◽  
PIERRE LATOUCHE

AbstractWe consider the task of simultaneous clustering of the two node sets involved in a bipartite network. The approach we adopt is based on use of the exact integrated complete likelihood for the latent blockmodel. Using this allows one to infer the number of clusters as well as cluster memberships using a greedy search. This gives a model-based clustering of the node sets. Experiments on simulated bipartite network data show that the greedy search approach is vastly more scalable than competing Markov chain Monte Carlo-based methods. Application to a number of real observed bipartite networks demonstrate the algorithms discussed.


2011 ◽  
pp. 483-489
Author(s):  
Xinhua Zhang ◽  
Novi Quadrianto ◽  
Kristian Kersting ◽  
Zhao Xu ◽  
Yaakov Engel ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document