摘要:

The filtering of two-dimensional (2-D) signals is treated using a self-tuning technique based on a truncated innovations model of the data. The resultant algorithms offer two key advantages over their fixed-coefficient counterparts. First, the self-tuning filters quickly and automatically set their own coefficients, thus avoiding the normal off-line design cycle. Secondly, self-tuning filters can function in an adaptive manner, such that the filter retunes to track time variations in the two-dimensional data. The self-tuning algorithms are formulated in terms of input/output models and thus complement the more usual state-space approach to the 2-D filtering problem.

ISSN:0020-7179    

DOI:10.1080/00207178508933375

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor

摘要:

The application of two-dimensional (2-D) self-tuning smoothers/filters to images is discussed. In particular, the way in which 2-D self-tuners are set up is treated, together with practical tips on the effective use of the algorithms. Also presented are results which show the self-tuners at work on a set of typical noise-corrupted pictures.

ISSN:0020-7179    

DOI:10.1080/00207178508933376

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor

摘要:

The paper describes the practical uses of two-dimensional (2-D) fc-step-ahead self-tuning prediction algorithms. Two distinct application areas are considered. The first concerns direct prediction/forecasting, applied to data with a strong periodic (or 'seasonal’) component. The second concerns the prediction of data from spatial scanning sensors or spatial sensor arrays. In both cases, the original data is usually one-dimensional in nature. The contribution of the paper is to show how, by treating the data as if it were two-dimensional in nature, a vast improvement in the quality of predictions is obtained. Moreover, because the 2-D predictors are self-tuning, the algorithms require virtually no user intervention and no prior filtering or pre-processing of the data.

ISSN:0020-7179    

DOI:10.1080/00207178508933377

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor

摘要:

A second-order discrete transfer function, with a pair of complex poles and one real zero, is assumed to be a model which characterizes the dynamic behaviour of a higher-order discrete system (perhaps, an existing system), or some idealized response. From expressions given in the paper is generated a table of numerical data which provides the means for determining the model's numerator and denominator coefficients from simple performance specifications given in either the time-, frequency- or complex z-domains, and vice-versa, and for converting specifications from one domain to another.

ISSN:0020-7179    

DOI:10.1080/00207178508933378

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor

摘要:

The purpose of the frequency response matching technique is to design a digital controller such that the frequency response of the resulting closed-loop system matches a specified frequency response model. The simplex method is employed to determine the controller's parameter values which minimize a function of the error between the two responses. This method permits constraints on the controller's gain and the pole-zero locations to be applied, for example, in order to reduce the highly oscillatory response of the output of the controller, a phenomenon which can be observed when applying other frequency response matching techniques. An example illustrating the use of the method, particularly at low sampling frequencies, is given.

ISSN:0020-7179    

DOI:10.1080/00207178508933379

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor

摘要:

It is shown that an estimate of the decay rate of a class of stable linear delay systems can be obtained without solving the transcendental equation and is, in addition less restrictive than that given by Mori et al. (1982).

ISSN:0020-7179    

DOI:10.1080/00207178508933380

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor

ISSN:0020-7179    

DOI:10.1080/00207178508933381

出版商:Taylor & Francis Group    

年代:1985

数据来源: Taylor