This paper proposes an efficient and convenient approach to frequency domain subspace identification for continuous-time systems. In the case of continuous-time models, the data matrices often become ill-conditioned i...
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This paper proposes an efficient and convenient approach to frequency domain subspace identification for continuous-time systems. In the case of continuous-time models, the data matrices often become ill-conditioned if we simply rewrite the Laplace operator s as s = jw where w denotes the frequency. To avoid the ill-conditioned problem, the operator w = ( s - b.α)/( s + b.α) is introduced such that the system can be identified based on a state-space model in the w -operator. And then the estimated w -operator state-space model can be transformed back to the common continuous-time state-space model. An instrumental variable matrix in the frequency domain is also proposed to obtain consistent estimate in the presence of measurement noise.
Usually, the subspace-based state-space system identification algorithms are focused on discrete-time models, which may cause some numerical problems when the sampling interval is small. This paper proposes an algorit...
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Usually, the subspace-based state-space system identification algorithms are focused on discrete-time models, which may cause some numerical problems when the sampling interval is small. This paper proposes an algorithm of subspace-based state-space system identification for continuous-time systems from sampled input-output data. The ω — operator ω = ( p - α)/( p + α) where p denotes a differential operator and α > 0, is introduced to avoid direct numerical differentiations. And the ω — operator state-space model identified by the 4SID method can be transformed back to the common continuous-time state-space model. The numerical superiority of the ω — operator approach compared to some other methods is verified through simulation study.
Secure communication systems based upon chaotic encryption of data have recently attracted interest. An efficient algorithm for improving the locking rate between receiver and transmitter of such a system has been rep...
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Secure communication systems based upon chaotic encryption of data have recently attracted interest. An efficient algorithm for improving the locking rate between receiver and transmitter of such a system has been reported previously K.A. Shore and D.T. Wright (1994) and we have given consideration to techniques for the control of the nonlinear dynamics of lasers in general V.N. Chizhevsky and S.I. Turovets (1994; 1993) and, in particular, laser diodes (L.N. Langley et al., 1995) which can function as practical transmitters in chaotic optical data encryption systems. An investigation is undertaken of the use of continuous optoelectronic feedback in selecting periodic dynamics in external cavity laser diodes, subject to conventional optical feedback. Other work has explored the control of chaos in external cavity laser diodes using occasional proportional feedback (G.R. Gray et al., 1993) and direct modulation (N. Watanabe and K. Karaki, 1995).
Inclusive baryon-antibaryon pair production was studied in two-photon events which were collected at the e + e - collider TRISTAN, and correspond to an integrated luminosity of 303 pb-1. Correlations between a baryon ...
A major limitation of the boundary element method (BEM) for the solution of electrical potential problems is the long computational time required. However, a large portion of the calculations involved can be viewed as...
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A major limitation of the boundary element method (BEM) for the solution of electrical potential problems is the long computational time required. However, a large portion of the calculations involved can be viewed as being parallel in nature and can therefore be computed concurrently. This paper makes an effort to increase the efficiency of the BEM process using transputer-based multiprocessor computing techniques. The algorithms developed may equally well be applied to any multiprocessor system. The application selected to demonstrate the technique is the solution of an electrostatic problem governed by a two-dimensional Laplace equation. A parallel algorithm for problem setup and field extraction using BEM is designed and implemented on a transputer array. Special attention is directed to the utilization of the parallel processors to achieve maximum efficiency. The analysis in this work concentrates on the communication strategies for passing data between processors as well as a consideration of the workload attributed to each processor. The parallel algorithms were implemented using 3L Parallel Fortran;however, the choice of topology for the overall BEM implementation was limited by the fact that certain parts of the algorithm could only utilize a pipeline configuration of processors. Comprehensive results for the parallel BEM algorithm are given and they are encouraging, indicating that parallel processing has much to offer when applied to the boundary element method.
The contingent negative variation (CNV), which is an evoked response in the human electroencephalogram (EEG), was measured for a number of Huntington's disease patients (HDs) and subjects at-risk of developing HD ...
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The contingent negative variation (CNV), which is an evoked response in the human electroencephalogram (EEG), was measured for a number of Huntington's disease patients (HDs) and subjects at-risk of developing HD (ARs), and for equal numbers of matched normal subjects. The sampled voltage response values and the duration of the CNV were then used as input data to Kohonen and ART2 unsupervised artificial neural networks to classify the subjects. The two methods gave similar results for the HDs vs normals which also agreed with the results of a cluster analysis. The results of attempting to identify abnormal ARs showed that the ART2 results showed partial agreement with the results of the Kohonen network and cluster analysis. The application of these unsupervised neural networks to the sub-typing of clinical categories appears to offer a relatively simple tool suitable for hardware implementation.< >
Describes a novel neural network architecture which, when applied to image data compression, is capable of real-time, one shot, vector quantization. The major feature of this system is the utilization of an adaptive t...
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Describes a novel neural network architecture which, when applied to image data compression, is capable of real-time, one shot, vector quantization. The major feature of this system is the utilization of an adaptive threshold mechanism. The architecture comprises a two-layer network and a winner-take-all cluster with adaptive thresholds. This system was used to generate a codebook for digital images.< >
This book constitutes the refereed proceedings of the Second;International Conference on Internet of Vehicles, IOV 2015, held in;Chengdu, China, in December 2015.;The 40 full papers presented were carefully reviewed a...
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ISBN:
(数字)9783319272931
ISBN:
(纸本)9783319272924
This book constitutes the refereed proceedings of the Second;International Conference on Internet of Vehicles, IOV 2015, held in;Chengdu, China, in December 2015.;The 40 full papers presented were carefully reviewed and selected from;128 submissions. They focus on the following topics: IOV architectures and;applications; intelligent mobility; V2V and M2M communications; and modeling and simulations.
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