We propose a generalized null space uncorrelated Fisher discriminant analysis (GNUFDA) technique integrating the uncorrelated discriminant analysis and weighted pairwise Fisher criterion. The GNUFDA can effectively deal with the small sample-size problem and perform satisfactorily when the dimensionality of the null space decreases with increase in the number of training samples per class and/or classes, C. The proposed GNUFDA can extract at most C-1 optimal uncorrelated discriminative vectors without being influenced by the null-space dimensionality. 相似文献
This paper presents a project undertaken for the European Space Agency (ESA). The project is developing a knowledge based system for planning and scheduling of activities for spacecraft assembly, integration and verification (AIV). The system extends to the monitoring of plan execution and the plan repair phases.
The objectives of the contract are to develop an operational kernel of a planning, scheduling and plan repair tool, called OPTIMUM-AIV, and to provide facilities which will allow individual projects to customize the kernel to suit its specific needs. The kernel shall consist of a set of software functionalities for assistance in the initial specification of the AIV plan, in the verification and generation of valid plans and schedules for the AIV activities, and in interactive monitoring and execution problem recovery for the detailed AIV plans. Embedded in OPTIMUM-AIV are external interfaces which allow integration with alternative scheduling systems and project databases.
The current status of the OPTIMUM-AIV project, as of May 1991, is that the architectural design of the system has been agreed on by ESTEC/ESA and detailed design and implementation is now underway, expecting a final delivery in October of 1991. 相似文献
The aim of this paper is to propose a new way to deal with observability of systems governed by ODEs, in a more general setting than the standard output equation.The primary finding is that observability over a time horizon reduces to single-valuedness of the vertical section of a set we name the observability kernel.The latter consists of the viability kernel of the output domain under the augmented system.The approach may be used either for global or local observability,to which available results on single-valuedness of multifunctions shall be applied in order to get necessary and/or sufficient characterizing conditions.Several examples are provided in order to illustrate the method. 相似文献
Abstract. This paper proposes a fully modified version of the spectral matrix estimator (and the long‐run variance estimator as a special case) proposed originally by Xiao and Linton [Journal of Time Series Analysis (2002) Vol. 23, pp. 215–250], and derives its asymptotic results. A striking feature of the modified spectral matrix estimator is to achieve the convergence rate of O(T?8/9) in the mean squared error (MSE), which is usually achieved under the fourth‐order spectral window. However, this estimator does not sacrifice the positive definiteness of the resulting estimate for the rate improvement; it is Hermitian and positive definite in finite samples by construction. The faster convergence rate is established by a multiplicative bias correction of the crude spectral estimator under the second‐order spectral window. The approximations to some sensible definitions of the MSE of the estimator and the bandwidths that minimize the asymptotic MSEs are also derived. Monte Carlo results indicate that for a wide variety of processes the modified spectral matrix estimator reduces the bias without inflating the variance and thus improves the MSE, compared with the crude, bias‐uncorrected estimator. 相似文献