In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying result...In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.展开更多
永磁同步电机电流环控制性能是决定驱动系统性能的核心因素。电流预测控制能够使永磁同步电机电流控制获得良好的动态响应,但是控制器电机模型参数与实际电机参数不一致会引起电流静差,导致系统效率降低,无法输出额定转矩,以及无法工作...永磁同步电机电流环控制性能是决定驱动系统性能的核心因素。电流预测控制能够使永磁同步电机电流控制获得良好的动态响应,但是控制器电机模型参数与实际电机参数不一致会引起电流静差,导致系统效率降低,无法输出额定转矩,以及无法工作在力矩控制模式等问题。该文根据永磁同步电机预测控制模型,详细分析了控制器电机模型参数误差对电流控制的影响,并提出了一种静差消除算法。这种方法主要适用于控制器中电机模型电感及磁链参数不准的情况,通过在d轴电流控制中加入误差积分作用,并根据q轴电流的响应,动态调整控制器电机模型磁链参数,消除了控制器电机模型参数不准引起的静差。通过仿真分析和在3.3 k W永磁同步电机驱动平台上的实验,验证了该算法的有效性。展开更多
根据谐波抑制兼无功功率补偿的要求,为达到最佳滤波效果和最小经济成本,提出了一种并联混合型注入式有源电力滤波器(Hybrid Active Power Filter with Injection Circuit,简称HAPFIC)。详细介绍了其工作原理、控制结构、有源和无源各部...根据谐波抑制兼无功功率补偿的要求,为达到最佳滤波效果和最小经济成本,提出了一种并联混合型注入式有源电力滤波器(Hybrid Active Power Filter with Injection Circuit,简称HAPFIC)。详细介绍了其工作原理、控制结构、有源和无源各部分参数的设计方法,并结合工程实际设计了HAPFIC的主要参数,利用PSIM仿真软件进行仿真实验,实验结果证明了设计方案的有效性和正确性。展开更多
针对带有外生变量的自回归移动平均模型(Autoregressive moving average with exogenous variable,ARMAX)的参数辨识问题提出一种两阶段辨识方法.首先通过偏差消除最小二乘方法辨识带有外生变量的自回归部分(Autoregressive part with e...针对带有外生变量的自回归移动平均模型(Autoregressive moving average with exogenous variable,ARMAX)的参数辨识问题提出一种两阶段辨识方法.首先通过偏差消除最小二乘方法辨识带有外生变量的自回归部分(Autoregressive part with exogenous variable,ARX),然后采用Durbin方法将移动平均部分(Moving average,MA)的参数辨识问题转换成一个长自回归模型(Long autoregressive,LAR)的参数辨识问题,并利用MA与等价LAR的参数对应关系直接得到MA参数,最后利用辨识出的MA参数计算出噪声方差.与扩展最小二乘法的数值仿真比较验证了这种两阶段辨识方法的有效性.展开更多
基金Project supported by the National Basic Research Program (973) of China (No. 2002CB312200) and the Center for Bioinformatics Pro-gram Grant of Harvard Center of Neurodegeneration and Repair,Harvard Medical School, Harvard University, Boston, USA
文摘In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.
文摘永磁同步电机电流环控制性能是决定驱动系统性能的核心因素。电流预测控制能够使永磁同步电机电流控制获得良好的动态响应,但是控制器电机模型参数与实际电机参数不一致会引起电流静差,导致系统效率降低,无法输出额定转矩,以及无法工作在力矩控制模式等问题。该文根据永磁同步电机预测控制模型,详细分析了控制器电机模型参数误差对电流控制的影响,并提出了一种静差消除算法。这种方法主要适用于控制器中电机模型电感及磁链参数不准的情况,通过在d轴电流控制中加入误差积分作用,并根据q轴电流的响应,动态调整控制器电机模型磁链参数,消除了控制器电机模型参数不准引起的静差。通过仿真分析和在3.3 k W永磁同步电机驱动平台上的实验,验证了该算法的有效性。
文摘根据谐波抑制兼无功功率补偿的要求,为达到最佳滤波效果和最小经济成本,提出了一种并联混合型注入式有源电力滤波器(Hybrid Active Power Filter with Injection Circuit,简称HAPFIC)。详细介绍了其工作原理、控制结构、有源和无源各部分参数的设计方法,并结合工程实际设计了HAPFIC的主要参数,利用PSIM仿真软件进行仿真实验,实验结果证明了设计方案的有效性和正确性。
文摘针对带有外生变量的自回归移动平均模型(Autoregressive moving average with exogenous variable,ARMAX)的参数辨识问题提出一种两阶段辨识方法.首先通过偏差消除最小二乘方法辨识带有外生变量的自回归部分(Autoregressive part with exogenous variable,ARX),然后采用Durbin方法将移动平均部分(Moving average,MA)的参数辨识问题转换成一个长自回归模型(Long autoregressive,LAR)的参数辨识问题,并利用MA与等价LAR的参数对应关系直接得到MA参数,最后利用辨识出的MA参数计算出噪声方差.与扩展最小二乘法的数值仿真比较验证了这种两阶段辨识方法的有效性.
