For the deficiency that the traditional single forecast methods could not forecast electronic equipment states, a combined forecast method based on the hidden Markov model（HMM） and least square support vector machin...For the deficiency that the traditional single forecast methods could not forecast electronic equipment states, a combined forecast method based on the hidden Markov model（HMM） and least square support vector machine（LS-SVM） is presented. The multi-agent genetic algorithm（MAGA） is used to estimate parameters of HMM to overcome the problem that the Baum-Welch algorithm is easy to fall into local optimal solution. The state condition probability is introduced into the HMM modeling process to reduce the effect of uncertain factors. MAGA is used to estimate parameters of LS-SVM. Moreover, pruning algorithms are used to estimate parameters to get the sparse approximation of LS-SVM so as to increase the ranging performance. On the basis of these, the combined forecast model of electronic equipment states is established. The example results show the superiority of the combined forecast model in terms of forecast precision,calculation speed and stability.展开更多
This paper deals with the robust guaranteed cost observer with guaranteed cost performance for a class of linear uncertain jump systems with state delay.The transition of the jumping parameters in systems is governed ...This paper deals with the robust guaranteed cost observer with guaranteed cost performance for a class of linear uncertain jump systems with state delay.The transition of the jumping parameters in systems is governed by a finite-state Markov process.Based on the stability theory in stochastic differential equations,a sufficient condition on the existence of the proposed robust guaranteed cost observer is derived.Robust guaranteed cost observers are designed in terms of a set of linear coupled matrix inequalities.A convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost observers.展开更多
文摘For the deficiency that the traditional single forecast methods could not forecast electronic equipment states, a combined forecast method based on the hidden Markov model（HMM） and least square support vector machine（LS-SVM） is presented. The multi-agent genetic algorithm（MAGA） is used to estimate parameters of HMM to overcome the problem that the Baum-Welch algorithm is easy to fall into local optimal solution. The state condition probability is introduced into the HMM modeling process to reduce the effect of uncertain factors. MAGA is used to estimate parameters of LS-SVM. Moreover, pruning algorithms are used to estimate parameters to get the sparse approximation of LS-SVM so as to increase the ranging performance. On the basis of these, the combined forecast model of electronic equipment states is established. The example results show the superiority of the combined forecast model in terms of forecast precision,calculation speed and stability.
基金Sponsored by the Scientific Research Foundation of Harbin Institute of Technology (Grant No.HIT.2003.02)the Chinese Outstanding Youth Science Foundation(Grant No. 69504002)
文摘This paper deals with the robust guaranteed cost observer with guaranteed cost performance for a class of linear uncertain jump systems with state delay.The transition of the jumping parameters in systems is governed by a finite-state Markov process.Based on the stability theory in stochastic differential equations,a sufficient condition on the existence of the proposed robust guaranteed cost observer is derived.Robust guaranteed cost observers are designed in terms of a set of linear coupled matrix inequalities.A convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost observers.
