This paper deals with the recursive identification of the parity space based fault detection systems. We propose two such algorithms that update the eigenstructure after every new measurement with significantly less c...
详细信息
This paper deals with the recursive identification of the parity space based fault detection systems. We propose two such algorithms that update the eigenstructure after every new measurement with significantly less computational cost. Its immediate application is in the design of adaptive parity space based residual generators. The method improves the fault detection performance against uncertain changes, especially the frequent shifts in operating points, or parameter variations. The algorithms are compared with the existing techniques and applied to the hybrid simulation platform of continuously stirred tank heater. (C) 2010 Elsevier Ltd. All rights reserved.
With the development of network technology, the reform of multimedia network teaching curriculum is accelerating, which promotes the reform of college teaching mode. At the same time, the existing multimedia teaching ...
详细信息
With the development of network technology, the reform of multimedia network teaching curriculum is accelerating, which promotes the reform of college teaching mode. At the same time, the existing multimedia teaching methods still have some problems, leading to the teaching effect can not be effectively improved. Therefore, on the basis of exploring the problems faced by multimedia teaching curriculum reform, this paper evaluates the new model based on structural recursive algorithm. The evaluation results show that this algorithm can effectively promote the reform process of multimedia teaching curriculum and help to improve the teaching effect.
An algorithm of the recursive parametric identification is analyzed, oriented to applying within noise-free systems. Its analytical form, conditions of the convergence and applications are specified. Theoretical infer...
详细信息
ISBN:
(纸本)9781479943159
An algorithm of the recursive parametric identification is analyzed, oriented to applying within noise-free systems. Its analytical form, conditions of the convergence and applications are specified. Theoretical inferences are confirmed by simulation results.
The global error is the identification error expressed expiIcItly as a function of all unknown system parameters, model parameters and external system inputs. It is used to transform the difficult problem of mean-squa...
详细信息
The global error is the identification error expressed expiIcItly as a function of all unknown system parameters, model parameters and external system inputs. It is used to transform the difficult problem of mean-square convergence and accuracy testing for recursive identification algorithms into a relatively simple problem of determining the properties of the solution for a polynomial equation. The method is introduced for the simple problem of closed-loop identification of time-discrete systems. Its full power is demonstrated for the case of the self-tuning regulator and self-tuning predictor.
The problem of recursive robust identification of linear discrete-time dynamic stochastic systems is discussed. Supposing approximately Gaussian system disturbance samples, a general form of robustified recursive iden...
详细信息
The problem of recursive robust identification of linear discrete-time dynamic stochastic systems is discussed. Supposing approximately Gaussian system disturbance samples, a general form of robustified recursive identification algorithms of stochastic approximation type, characterized by an adequate nonlinear residual transformation, is defined. In order to improve the convergence rate, especially on short data sequences, the weighting matrix of the algorithm is derived by performing step-by-step optimization of a predefined empirical criterion. The convergence of the estimates w.p.l. is established theoretically by using martingale theory. The theoretical results are followed by extensive Monte Carlo simulation results, providing a basis for making a precise judgement of real practical robustness of the algorithms. Important relationships between parameters describing the algorithms are pointed out.
At the heart of adaptive/predictive process control is the process identification algorithm. recursive least squares, the most popular identification algorithm, has severe limitations that restrict its use in many ind...
详细信息
There is currently a renewed interest in the Bayesian predictive approach to statistics. This paper offers a review on foundational concepts and focuses on "predictive modeling," which by directly reasoning ...
详细信息
There is currently a renewed interest in the Bayesian predictive approach to statistics. This paper offers a review on foundational concepts and focuses on "predictive modeling," which by directly reasoning on prediction bypasses inferential models or may characterize them. We detail predictive characterizations in exchangeable and partially exchangeable settings, for a large variety of data structures, and hint at new directions. The underlying concept is that Bayesian predictive rules are probabilistic learning rules, formalizing through conditional probability how we learn on future events given the available information. This concept has implications in any statistical problem and in inference, from classic contexts to less explored challenges, such as providing Bayesian uncertainty quantification to predictive algorithms in data science, as we show in the last part of the paper. The paper not only gives a historical overview but also includes a few new results, presents some recent developments and poses some open questions.
We here address the issue of ground clutter rejection for the detection of slowly moving targets in a non-side looking (NSL) array configuration airborne radar. The optimum space-time adaptive processing (STAP) filter...
详细信息
We here address the issue of ground clutter rejection for the detection of slowly moving targets in a non-side looking (NSL) array configuration airborne radar. The optimum space-time adaptive processing (STAP) filter needs the knowledge of the inverse of the space-time covariance matrix. In practice, it is unknown and has to be estimated. The most popular approximated method is the sample matrix inversion (SMI) method which consists in inverting the covariance matrix estimated by an average of the sample matrix over the secondary range cells. This estimator is unbiased in case of i.i.d. data. In an NSL configuration, the clutter power spectrum is range dependent and the data are consequently not i.i.d. We here present a solution to mitigate this range dependency of the data: the range recursive subspace-based algorithms. They are used in two architectures: a fully and a partially adaptive ones. Then a new range-recursive algorithm using Taylor series expansion is investigated. The performance of these algorithms are compared with that of the conventional STAP algorithms in term of SINR loss. (C) 2009 Elsevier B.V. All rights reserved.
The convergence properties of recently developed recursive subspace identification methods are investigated in this paper. The algorithms operate on the basis of instrumental variable (IV) versions of the propagator m...
详细信息
The convergence properties of recently developed recursive subspace identification methods are investigated in this paper. The algorithms operate on the basis of instrumental variable (IV) versions of the propagator method for signal subspace estimation. It is proved that, under suitable conditions on the input signal and the system, the considered recursive subspace identification algorithms converge to a consistent estimate of the propagator and, by extension, to the state-space system matrices. (c) 2007 Elsevier Ltd. All rights reserved.
Using the proposed factorizations of discrete cosine transform (DCT) matrices, fast and recursive algorithms are stated. In this paper, signal flow graphs for the n-point DCT II and DCT IV algorithms are introduced. T...
详细信息
Using the proposed factorizations of discrete cosine transform (DCT) matrices, fast and recursive algorithms are stated. In this paper, signal flow graphs for the n-point DCT II and DCT IV algorithms are introduced. The proposed algorithms yield exactly the same results as with standard DCT algorithms but are faster. The arithmetic complexity and stability of the algorithms are explored, and improvements of these algorithms are compared with previously existing fast and stable DCT algorithms. A parallel hardware computing architecture for the DCT II algorithm is proposed. The computing architecture is first designed, simulated, and prototyped using a 40-nm Xilinx Virtex-6 FPGA and thereafter mapped to custom integrated circuit technology using 0.18-m CMOS standard cells from Austria Micro Systems. The performance trade-off exists between computational precision, chip area, clock speed, and power consumption. This trade-off is explored in both FPGA and custom CMOS implementation spaces. An example FPGA implementation operates at clock frequencies in excess of 230MHz for several values of system word size leading to real-time throughput levels better than 230 million 16-point DCTs per second. Custom CMOS-based results are subject to synthesis and place-and-route steps of the design flow. Physical silicon fabrication was not conducted due to prohibitive cost.
暂无评论