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无编辑摘要
|收敛速度比幂律快 <math>\langle A\rangle > N^x \forall x</math>
|收敛速度比幂律快 <math>\langle A\rangle > N^x \forall x</math>
|收敛速度比幂律快, <math>\langle\nu\rangle > N^x \forall x</math>
|<math>\langle\nu\rangle > N^x \forall x</math>
|首个数学上的证据
|首个数学上的证据
|2002
|2002
| 与系统大小成线性关系,
|与系统大小成线性关系,
|与系统大小成线性关系, <math>\langle\nu\rangle \sim N</math>
|<math>\langle\nu\rangle \sim N</math>
|
|
|快于线性关系,
|快于线性关系,
|快于线性关系, <math>\langle\nu\rangle > N^x</math> <math>x > 1</math>
|<math>\langle\nu\rangle > N^x</math> <math>x > 1</math>
|
|
|超多项式增长,
|超多项式增长,
|超多项式增长, <math>\langle\nu\rangle > N^x \forall x</math>
|<math>\langle\nu\rangle > N^x \forall x</math>
|提供数学证明
|提供数学证明
|收敛速度比幂律快, <math>\langle A\rangle > N^x \forall x</math>
|收敛速度比幂律快, <math>\langle A\rangle > N^x \forall x</math>
|收敛速度比幂律快, <math>\langle\nu\rangle > N^x \forall x</math>
|<math>\langle\nu\rangle > N^x \forall x</math>
|
|
*The '''Partially-Observed Boolean Dynamical System (POBDS)'''<ref>{{Cite journal|last=Imani|first=M.|last2=Braga-Neto|first2=U. M.|date=2017-01-01|title=Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems|journal=IEEE Transactions on Signal Processing|volume=65|issue=2|pages=359–371|doi=10.1109/TSP.2016.2614798|issn=1053-587X|arxiv=1702.07269|bibcode=2017ITSP...65..359I}}</ref><ref>{{Cite book|pages=972–976|last=Imani|first=M.|last2=Braga-Neto|first2=U. M.|language=en-US|doi=10.1109/GlobalSIP.2015.7418342|chapter=Optimal state estimation for boolean dynamical systems using a boolean Kalman smoother|year=2015|isbn=978-1-4799-7591-4|title=2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)}}</ref><ref>{{Cite book|last=Imani|first=M.|last2=Braga-Neto|first2=U. M.|language=en-US|doi=10.1109/ACC.2016.7524920|title=2016 American Control Conference (ACC)|pages=227–232|year=2016|isbn=978-1-4673-8682-1}}</ref><ref>{{Cite book|last=Imani|first=M.|last2=Braga-Neto|first2=U.|date=2016-12-01|title=Point-based value iteration for partially-observed Boolean dynamical systems with finite observation space|journal=2016 IEEE 55th Conference on Decision and Control (CDC)|pages=4208–4213|doi=10.1109/CDC.2016.7798908|isbn=978-1-5090-1837-6}}</ref> signal model differs from all previous deterministic and stochastic Boolean network models by removing the assumption of direct observability of the Boolean state vector and allowing uncertainty in the observation process, addressing the scenario encountered in practice.
*The '''Partially-Observed Boolean Dynamical System (POBDS)'''<ref>{{Cite journal|last=Imani|first=M.|last2=Braga-Neto|first2=U. M.|date=2017-01-01|title=Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems|journal=IEEE Transactions on Signal Processing|volume=65|issue=2|pages=359–371|doi=10.1109/TSP.2016.2614798|issn=1053-587X|arxiv=1702.07269|bibcode=2017ITSP...65..359I}}</ref><ref>{{Cite book|pages=972–976|last=Imani|first=M.|last2=Braga-Neto|first2=U. M.|language=en-US|doi=10.1109/GlobalSIP.2015.7418342|chapter=Optimal state estimation for boolean dynamical systems using a boolean Kalman smoother|year=2015|isbn=978-1-4799-7591-4|title=2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)}}</ref><ref>{{Cite book|last=Imani|first=M.|last2=Braga-Neto|first2=U. M.|language=en-US|doi=10.1109/ACC.2016.7524920|title=2016 American Control Conference (ACC)|pages=227–232|year=2016|isbn=978-1-4673-8682-1}}</ref><ref>{{Cite book|last=Imani|first=M.|last2=Braga-Neto|first2=U.|date=2016-12-01|title=Point-based value iteration for partially-observed Boolean dynamical systems with finite observation space|journal=2016 IEEE 55th Conference on Decision and Control (CDC)|pages=4208–4213|doi=10.1109/CDC.2016.7798908|isbn=978-1-5090-1837-6}}</ref> signal model differs from all previous deterministic and stochastic Boolean network models by removing the assumption of direct observability of the Boolean state vector and allowing uncertainty in the observation process, addressing the scenario encountered in practice.
==Application of Boolean Networks==
==Application of Boolean Networks ==
布尔网络的应用<br>
布尔网络的应用<br>
{{Reflist|30em}}
{{Reflist|30em}}
* Dubrova, E., Teslenko, M., Martinelli, A., (2005). *[http://dl.acm.org/citation.cfm?id=1129670 Kauffman Networks: Analysis and Applications], in "Proceedings of International Conference on Computer-Aided Design", pages 479-484.<!-- to be cited or not -->
*Dubrova, E., Teslenko, M., Martinelli, A., (2005). *[http://dl.acm.org/citation.cfm?id=1129670 Kauffman Networks: Analysis and Applications], in "Proceedings of International Conference on Computer-Aided Design", pages 479-484.<!-- to be cited or not -->