This paper describes B-spline interpolation and compares it with other reconstruction methods, especially in three-dimensional space. We first consider the B-spline bases in the terms of convolution in signal processi...
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This paper describes B-spline interpolation and compares it with other reconstruction methods, especially in three-dimensional space. We first consider the B-spline bases in the terms of convolution in signal processing. The presented analysis requires careful usage of continuous and discrete representation of B-spline. Emphasis is given to the important difference between B-spline interpolation and approximation. The difference is shown through frequency domain analysis, so we derive frequency responses of the B-spline interpolation and approximation. We conclude by demonstrating the use of several reconstruction filters and appropriate gradient estimators in volume rendering. Exact reconstruction in volume visualization is very important in many industrial applications, such as material cavity control.
The volume data is generally in the form of the large array of numbers. In order to render the object hidden in the volumetric data, we need to reconstruct or interpolate data values between the samples. The novelty p...
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The volume data is generally in the form of the large array of numbers. In order to render the object hidden in the volumetric data, we need to reconstruct or interpolate data values between the samples. The novelty presented in this paper is B-spline interpolation in the volumetric space. We show that this approach is better than currently used methods. We also present a hybrid approach, analyze this approach in frequency domain and compare it to B-spline interpolation. To enhance the quality during the volume visualization process it is important to enhance the quality of the reconstruction. It is of crucial importance to explore different undesired effects. If better reconstruction is performed the more accurate result of volume visualization process is achieved.
This paper develops an evolutionary algorithm-based methodology for robust DC servomotor control system design. Unlike conventional methods, the evolutionary design technique is capable of simultaneously solving mixed...
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This paper develops an evolutionary algorithm-based methodology for robust DC servomotor control system design. Unlike conventional methods, the evolutionary design technique is capable of simultaneously solving mixed-sensitivity optimization and incorporating practical time-domain constraints without the need for a differentiable performance index. Experimental results show that the evolutionary design can include practical constraints such as actuator saturation and offer an excellent closed-loop performance with good robustness in the presence of nonlinear constraints, disturbances, and plant uncertainties.
Change-point detection is a fundamental problem in many areas of signal segmentation, feature extraction and classification. There are various statistical methods that can be applied to estimate boundaries of signal s...
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Change-point detection is a fundamental problem in many areas of signal segmentation, feature extraction and classification. There are various statistical methods that can be applied to estimate boundaries of signal segments. The paper presents another method based upon the wavelet transform and signal decomposition used to detect signal irregularities. This approach can be very efficient if the initial wavelet function is carefully chosen. Basic methods presented in the paper are verified for simulated sequences at first and then used for biomedical signal segmentation. Resulting algorithms are written in the MATLAB environment.
A dynamical mathematical model of a water supply plant based on lumped parameters is described. A concept of its control system is proposed that ensures output pressure stabilisation under conditions of variable water...
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A dynamical mathematical model of a water supply plant based on lumped parameters is described. A concept of its control system is proposed that ensures output pressure stabilisation under conditions of variable water consumption and variable water recourses. The control system consists of inner control loops which control the flow of each pump station and of a superimposed control loop that controls the output pressure of the water supply plant. The pressure controller calculates the cumulative reference value of the water flow for all controlled pumps and from this value an algorithm for the flow distribution calculates the reference flow for each inner loop, taking into account the level of water accumulation in each water well. control performances of output pressure obtained by a conventional PI controller and a fuzzy logic based controller are compared.
The basic principles of the self-tuning generalized predictive controller (GPC) and the self-tuning pole placement controller are presented. A laboratory shell-and-tube heat exchanger is used to test the properties of...
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The basic principles of the self-tuning generalized predictive controller (GPC) and the self-tuning pole placement controller are presented. A laboratory shell-and-tube heat exchanger is used to test the properties of the presented controllers. The self-tuning GPC were compared with the self-tuning pole placement controller regarding their parameter adjustment complexity, reference and disturbance step responses and robustness to differences between the real process and its mathematical model.
The model based fault detection and identification scheme for the rudder servo system as the actuator in the closed loop course keeping control system is presented. The nonlinear process model that enables description...
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The model based fault detection and identification scheme for the rudder servo system as the actuator in the closed loop course keeping control system is presented. The nonlinear process model that enables description of a wide class of fault types is given and the fault function as the residual for detecting and identifying the fault is introduced. A fault detection scheme with variable thresholds is suggested and its performance has been tested via simulation in the presence of modeling uncertainty and noise. A fault identification scheme based on comparison between the fault function estimate and the output of a predefined analytical fault model is suggested.
The aim of this article is to verify, in the economic feasibility analysis phase, the factors which either promote or limit the successful introduction and implementation of new information technology, and to do this ...
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The aim of this article is to verify, in the economic feasibility analysis phase, the factors which either promote or limit the successful introduction and implementation of new information technology, and to do this by means of a case study. These factors are studied in the framework of the interpretative theory of the evaluation of information technology and the theory of reasoned action in the decision taking process.
作者:
Zoran VukićEdin OmerdićLjubomir KuljacaUniversity of Zagreb
Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering in Automation Unska 3 HR-10000 Zagreb Croatia University of Tuzla
Faculty of Electrical and Mechanical Engineering Department of Control Engineering in Automation Franjevačka 2 BH-75000 Tuzla Bosnia and Herzegovina
Improved 2-input fuzzy autopilot for ship course control and 3-input fuzzy autopilot for track-keeping are proposed. Nonlinear model of a ship and a steering subsystem is used. The 3-input fuzzy autopilot uses heading...
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Improved 2-input fuzzy autopilot for ship course control and 3-input fuzzy autopilot for track-keeping are proposed. Nonlinear model of a ship and a steering subsystem is used. The 3-input fuzzy autopilot uses heading signal, yaw rate signal and lateral offset from the nominal track to produce a command rudder angle. Input variable fuzzyfication, fuzzy associative memory rules and output set defuzzyfication are described. Obtaining of FAM rules for 3-input fuzzy is described. Dynamical behavior of 2 and 3-input fuzzy autopilot is compared. The influence of wave disturbance, sea current and external disturbance from a passing ship on track-keeping performance was analyzed.
Noise reduction, together with signal modelling, classification and prediction, forms a basic problem in many engineering, biomedical and econometric systems. The paper summarizes basic adaptive methods based upon the...
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Noise reduction, together with signal modelling, classification and prediction, forms a basic problem in many engineering, biomedical and econometric systems. The paper summarizes basic adaptive methods based upon the application of artificial neural networks simplified in many cases to an adaptive linear element only. Adaptive noise cancelling algorithms by such finite impulse response (FIR) filters are studied in the first part of the paper both for the case that a reference signal is known and for reference-free structures. Resulting signals are compared with those obtained by noise rejection in the wavelet transform domain either based upon signal decomposition and reconstruction using properly chosen threshold levels for signal modification or incorporating adaptive FIR filtering. Signals preprocessed in this way are then used for their segmentation and classification to verify the effect of signal denoising. Methods presented in the paper are used for simulated signals at first and then applied to the processing of real signals representing physiological signals and technological time series.
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