To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is intro...To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is introduced and a fuzzy adaptive strong tracking cubature Kalman filter( FASTCKF) based on fuzzy logic controller is proposed. This method monitors residual absolute mean and standard deviation of each measurement component with fuzzy logic adaptive controller( FLAC),and adjusts the softening factor matrix dynamically by fuzzy rules,which is capable to modify suboptimal fading factor of STF adaptively and improve the filter's robust adaptive capacity. The simulation results show that the improved filtering performance is superior to the conventional square root cubature Kalman filter( SCKF) and the strong tracking square root cubature Kalman filter( STSCKF).展开更多
In the finance market, risk happened in two pattern. In one case, extreme volatility together with a short balance time leads to a great panic to the market. On the contrary, if the volatility is smaller, the time per...In the finance market, risk happened in two pattern. In one case, extreme volatility together with a short balance time leads to a great panic to the market. On the contrary, if the volatility is smaller, the time period will usually be longer. It will bring many infections to various related fields,which causes wider range influences to the economy. Both cases hurt financial market and the economy itself deeply. In this paper, we developed a novel market regulation method in which the conflict of fluctuation time and volatility will be balanced. It describes a way to compute a portfolio of relatively short time period together with smaller fluctuation volatility by using a general prediction algorithm based on overshoot in cybernetics. It can also give explanation to counter-cyclical supervision theory and macro-prudential regulation. Furthermore, it can provide numerical operation guide for countercyclical supervision theory and macro-prudential regulation.展开更多
基金National Natural Science Foundations of China(Nos.51175082,60874092,51375088)
文摘To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is introduced and a fuzzy adaptive strong tracking cubature Kalman filter( FASTCKF) based on fuzzy logic controller is proposed. This method monitors residual absolute mean and standard deviation of each measurement component with fuzzy logic adaptive controller( FLAC),and adjusts the softening factor matrix dynamically by fuzzy rules,which is capable to modify suboptimal fading factor of STF adaptively and improve the filter's robust adaptive capacity. The simulation results show that the improved filtering performance is superior to the conventional square root cubature Kalman filter( SCKF) and the strong tracking square root cubature Kalman filter( STSCKF).
基金Supported by the National Natural Science Foundation of China(71673214)National Post-doctor Foundation of China(2015M582627)China Scholarship Council(201308615060)
文摘In the finance market, risk happened in two pattern. In one case, extreme volatility together with a short balance time leads to a great panic to the market. On the contrary, if the volatility is smaller, the time period will usually be longer. It will bring many infections to various related fields,which causes wider range influences to the economy. Both cases hurt financial market and the economy itself deeply. In this paper, we developed a novel market regulation method in which the conflict of fluctuation time and volatility will be balanced. It describes a way to compute a portfolio of relatively short time period together with smaller fluctuation volatility by using a general prediction algorithm based on overshoot in cybernetics. It can also give explanation to counter-cyclical supervision theory and macro-prudential regulation. Furthermore, it can provide numerical operation guide for countercyclical supervision theory and macro-prudential regulation.
