1.
2.
Krishnamurthy, Vikram, et al.
(author)
Factorizations that relax the positive real condition in continuous-time and fast-sampled ELS schemes
1990
In: International journal of adaptive control and signal processing (Print). - : Wiley. - 0890-6327 .- 1099-1115. ; 4:5, s. 389-414
Journal article (peer-reviewed) abstract
This paper proposes extended least-squares (ELS) for ARMAX model identification of continuous-time and certain discrete-time systems. The schemes have a relaxed strictly positive real (SPR) condition for global convergence. The relaxed SPR scheme is achieved by introducing overparametrization and prefiltering but without introducing ill-conditioning. The schemes presented are the first such proposed for continuous-time systems. The concepts developed in continuous time carry through to fast-sampled continuous-time systems and associated discrete-time ELS algorithms. For such situations, in comparison with previously proposed discrete-time schemes, the degree of overparametrization required in the proposed scheme of this paper is significantly lower. The reduction is achieved by using more suitable prefiltering and overparametrization techniques than previously proposed. We also establish the persistence of excitation (PE) of the regression vectors in the proposed ELS schemes to assure strong consistency, obtain convergence rates and provide robustness to unmodelled dynamics. To prove the PE of continuous-time regression vectors, we develop output reachability characterization for MIMO linear continuous-time systems.
3.
Brunnström, Kjell, et al.
(author)
Scale and Resolution in Active Analysis of Local Image Structure
1990
In: Image and Vision Computing. - : Elsevier. ; 8:4, s. 289-296
Journal article (peer-reviewed) abstract
Focus-of-attention is extremely important in human visual perception. If computer vision systems are to perform tasks in a complex, dynamic world they will have to be able to control processing in a way that is analogous to visual attention in humans. Problems connected to foveation (examination of selected regions of the world at high resolution) are examined. In particular, the problem of finding and classifying junctions from this aspect is considered. It is shown that foveation as simulated by controlled, active zooming in conjunction with scale-space techniques allows for robust detection and classification of junctions.
4.
Stranneby, Dag, et al.
(author)
Adaptive Frequency Hopping in HF Environments
1993
In: IEEE Military Communications Conference, 1993. MILCOM '93. - New Jersey : IEEE. - 0780309537 ; , s. 338-341
Conference paper (peer-reviewed) abstract
A frequency hopping scheme (1 bit per chip) is proposed and studied in some detail for channels in the HF-band. This band is subject to interference that varies with time and frequency, due to varying transmission and channel propagation conditions. To make efficient use of the available channel resource an adaptive frequency hopping algorithm has been implemented by means of a neural network to make use of the available channel information from the link quality analysis (LQA) in selecting the frequency slot in contrast to having a uniformly distrinuted selection process. The algorithm proposed combines the advantages of low probability of detection during transmission and reduced fading and interference disturbance when detecting transmitted signals. The disturbances not eliminated by the channel selection is further reduced by using block codes with first order soft decision decoding. The results on residual bit error rate and average signal to interference ratio are promising with an overall reduction in bit error rate of more than two orders of magnitude at moderate signal to noise and signal to interference ratios for a course channel model based upon the results by P. J. Laycock et al. (1988)
5.
Ljung, Lennart, 1946-
(author)
Identification of Linear Systems
1993
In: CAD for Control Systems. - New York : Marcel Dekker. - 082479060X ; , s. 147-165
Book chapter (other academic/artistic)
6.
Wahlberg, Bo
(author)
Robust Frequency Domain Fault Detection/Diagnosis
1990
In: Proceedings of the 11th IFAC World Congress. ; , s. 74-79
Conference paper (peer-reviewed) abstract
Undermodelling can lead to poor behavior of fault detection (diagnosis) algorithms based on estimated parametric models. The aim of this paper is to study how to reduce this problem by working in the frequency domain and using flexible models. Simple and practically appealing frequency domain fault detection/diagnosis schemes are derived using recent results of Ljung (1987) on a high-order black-box identification theory.
7.
8.
9.
Åström, Karl J., et al.
(author)
Facing the Challenge of Computer Science in the Industrial Applications of Control
1992
Reports (other academic/artistic) abstract
Control, signal processing, and more generally "systems" industries ignore the boundaries we have in the academic world between control, signal processing, and computer sciences. Industries think of "hardware" (electronics or computers) and "software", making little distinction between algorithms development and implementation of them. Acting as a chariman of the IFAC Technical Committee on Theory for the triennium 1990-1993, Albert Benveniste proposed in the fall of 1989 this project to investigate some fundamental questions raised by the above mentioned facts. Since CDC'90 this has been approved as a joint IEEE/CSS-IFAC project managed by the above listed group of people. A detailed progress report of the project has been written in March 20, 1991, followed by a brief update in October 19, 1991. This is summary of the conclusions of the report. Additional detailed information on the project is found in the bibliography.
10.
Gunnarsson, Svante, et al.
(author)
Some asymptotic results in recursive identification using Laguerre models
1991
In: International Journal of Adaptive Control and Signal Processing. - : Wiley. - 0890-6327 .- 1099-1115. ; 5:5, s. 313-333
Journal article (peer-reviewed) abstract
This paper deals with recursive identification of time-varying systems using Laguerre models. Laguerre models generalize finite impulse response (FIR) models by using a priori information about the dominating time constants of the system to be identified. Three recursive algorithms are considered: the stochastic gradient algorithm, the recursive least squares algorithm and a Kalman-filter-like recursive identification algorithm. Simple and explicit expressions for the model quality are derived under the assumptions that the system varies slowly, that the model is updated slowly and that the model order is high. The derived expressions show how the use of Laguerre models affects the model quality with respect to tracking capability and disturbance rejection.