A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establ...A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.展开更多
The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewis...The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewise affine system is that each separated region and each unknown parameter vector are all needed to be determined simultaneously. Then, firstly, in order to achieve the identification goal, a multi-class classification process is proposed to determine each separated region. As the proposed multi-class classification process is the same with the classical data clustering strategy, the multi-class classification process can combine the first order algorithm of convex optimization, while achieving the goal of the classification process. Secondly, a zonotope parameter identification algorithm is used to construct a set, which contains the unknown parameter vector. In this zonotope parameter identification algorithm, the strict probabilistic description about the external noise is relaxed, and each unknown parameter vector is also identified. Furthermore, this constructed set is consistent with the measured output and the given bound corresponding to the noise. Thirdly, a sufficient condition about guaranteeing our derived zonotope not growing unbounded with iterations is formulated as an explicit linear matrix inequality. Finally, the effectiveness of this zonotope parameter identification algorithm is proven through a simulation example.展开更多
为了实现永磁同步直线电机PMSLM(permanent magnet synchronous linear motor)高精度的多电气参数在线辨识,提出了一种基于双模型的递推最小二乘电气参数在线辨识算法。首先,根据电机的dq轴电压方程分别建立了辨识定子电阻、永磁体磁链...为了实现永磁同步直线电机PMSLM(permanent magnet synchronous linear motor)高精度的多电气参数在线辨识,提出了一种基于双模型的递推最小二乘电气参数在线辨识算法。首先,根据电机的dq轴电压方程分别建立了辨识定子电阻、永磁体磁链的模型1和辨识q轴电感、d轴电感的模型2,并将2个辨识模型循环结合。其次,基于上述双模型结构,采用递推最小二乘算法实现电气参数在线辨识,并针对PMSLM运行时存在大量动态过程的特性,提出一种具有饱和特性的分段变遗忘因子;然后,对功率开关非理想因素导致的误差电压进行补偿,进一步提高了辨识的精准度;最后,仿真和实验结果证明了该辨识算法的有效性,且具有收敛速度快、辨识结果精度高、多工况适用等优点。展开更多
文摘A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.
文摘The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewise affine system is that each separated region and each unknown parameter vector are all needed to be determined simultaneously. Then, firstly, in order to achieve the identification goal, a multi-class classification process is proposed to determine each separated region. As the proposed multi-class classification process is the same with the classical data clustering strategy, the multi-class classification process can combine the first order algorithm of convex optimization, while achieving the goal of the classification process. Secondly, a zonotope parameter identification algorithm is used to construct a set, which contains the unknown parameter vector. In this zonotope parameter identification algorithm, the strict probabilistic description about the external noise is relaxed, and each unknown parameter vector is also identified. Furthermore, this constructed set is consistent with the measured output and the given bound corresponding to the noise. Thirdly, a sufficient condition about guaranteeing our derived zonotope not growing unbounded with iterations is formulated as an explicit linear matrix inequality. Finally, the effectiveness of this zonotope parameter identification algorithm is proven through a simulation example.
文摘为了实现永磁同步直线电机PMSLM(permanent magnet synchronous linear motor)高精度的多电气参数在线辨识,提出了一种基于双模型的递推最小二乘电气参数在线辨识算法。首先,根据电机的dq轴电压方程分别建立了辨识定子电阻、永磁体磁链的模型1和辨识q轴电感、d轴电感的模型2,并将2个辨识模型循环结合。其次,基于上述双模型结构,采用递推最小二乘算法实现电气参数在线辨识,并针对PMSLM运行时存在大量动态过程的特性,提出一种具有饱和特性的分段变遗忘因子;然后,对功率开关非理想因素导致的误差电压进行补偿,进一步提高了辨识的精准度;最后,仿真和实验结果证明了该辨识算法的有效性,且具有收敛速度快、辨识结果精度高、多工况适用等优点。
文摘采用自主水下航行器(Autonomous Underwater Vehicle,AUV)磁测平台可开展海洋地磁场测量、水下磁性目标探测和识别等工作,AUV磁测平台具有广阔的应用前景,但目前AUV载体磁干扰补偿技术研究尚不成熟,制约着水下航行器测磁精度。基于磁测平台抗磁干扰基本原理,提出一种基于线性种群规模缩减和成功历史的参数自适应差分进化(Success History-based Adaptive Differential Evolution with Linear Population Size Reduction,L-SHADE)算法的AUV载体磁干扰参数辨识的数值模拟方法。用磁偶极子和旋转椭球壳混合模型来等效模拟AUV载体磁干扰,通过模拟航行获得多组磁测数据,据此建立磁干扰参数辨识模型,并采用L-SHADE算法求解。通过数值模拟实验定量分析研究磁测平台测磁精度随磁传感器、平台姿态及航向等误差的传播规律。研究结果表明:当磁传感器测量精度为10 nT、姿态测量精度为0.01°、航向测量精度为0.1°时,测磁误差可小于100 nT。设计的AUV磁测平台抗干扰试验表明,地磁场总量最大相对误差为1.07%。
