Image segmentation, feature extraction and image components classification form a fundamental problem in many applications of multi-dimensional signal processing. The paper is devoted to the use of watershed transform...
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Image segmentation, feature extraction and image components classification form a fundamental problem in many applications of multi-dimensional signal processing. The paper is devoted to the use of watershed transform for image segmentation in connection with wavelet transform allowing image de-noising and image components feature extraction. Proposed methods are applied for biomedical image analysis and processing. The study of MR image segmentation devoted to the detection of its specific components results in the proposal of the appropriate image preprocessing to reduce problems of its oversegmentation. Resulting algorithms include the use of wavelet transform and gradient methods in the preprocessing stage. Proposed algorithms are verified for simulated images and applied for a selected MR biomedical images containing different structures.
State tree structures (STS) are an adaptation of statecharts to supervisory control theory. STSLib is a C++ library that we have developed to support the symbolic analysis and synthesis of STS. This paper presents a s...
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State tree structures (STS) are an adaptation of statecharts to supervisory control theory. STSLib is a C++ library that we have developed to support the symbolic analysis and synthesis of STS. This paper presents a short introduction to the library, and then applies the library to two benchmarks: (1) cat and mouse tower (CMT), (2) dining philosophers (DP). We demonstrate that STSLib can design optimal nonblocking supervisors for systems of state size up to 10 626 , and the resulting controllers are tractable and readily comprehensible.
In this paper a further step towards a novel approach to adaptive nonlinear control developed at Budapest Tech in the past few years is reported. Its main advantage in comparison with the complicated Lyapunov function...
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ISBN:
(纸本)9781424428755
In this paper a further step towards a novel approach to adaptive nonlinear control developed at Budapest Tech in the past few years is reported. Its main advantage in comparison with the complicated Lyapunov function based techniques is that its fundament is some simple geometric consideration allowing to formulate the control task as a Fixed Point Problem for the solution of which various Contractive Mappings can be created that generate Iterative Cauchy Sequences for Single Input - Single Output (SISO) systems. These sequences can converge to the fixed points that are the solutions of the control tasks. Recently alternative potential solutions were proposed and sketched by the use of special functions built up of the "response function" of the excited system under control. These functions have almost constant values apart from a finite region in which they have a "wrinkle" in the vicinity of the desired solution that is the "proper" fixed point of these functions. It was shown that at one of their sides these fixed points were repulsive, while at the opposite side they were attractive. It was shown, too, that at the repulsive side another, so called "false" fixed points were present that were globally attractive, with the exception of the basins of attraction of the "proper" ones. This structure seemed to be advantageous because no divergences could occur in the iterations, the convergence to the "false" values could easily be detected, and by using some ancillary tricks in the most of the cases the solutions could be kicked from the wrong fixed points into the basins of attraction of the "proper ones". It was expected that via adding simple rules to the application of these transformations good adaptive control can be developed. However, due to certain specialties of these functions practical problems arose. In the present paper novel transformations are presented that seem to evade these difficulties. Their applicability is illustrated via simulations in the ad
This paper deals with approximate value iteration (AVI) algorithms applied to discounted dynamic (DP) programming problems. The so-called Bellman residual is shown to be convex in the Banach space of candidate solutio...
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This paper deals with approximate value iteration (AVI) algorithms applied to discounted dynamic (DP) programming problems. The so-called Bellman residual is shown to be convex in the Banach space of candidate solutions to the DP problem. This fact motivates the introduction of an AVI algorithm with local search that seeks an approximate solution in a lower dimensional space called approximation architecture. The optimality of a point in the approximation architecture is characterized by means of convex optimization concepts and necessary and sufficient conditions to global optimality are derived. To illustrate the method, two examples are presented which were previously explored in the literature.
In this paper, we present a pedestrian detection approach using spatial histograms of oriented gradients feature. As spatial histograms of oriented gradients consist of marginal distributions of an image over local an...
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In this paper, we present a pedestrian detection approach using spatial histograms of oriented gradients feature. As spatial histograms of oriented gradients consist of marginal distributions of an image over local and global patches, they can preserve shape and contour of a pedestrian simultaneously. There are two main contributions in this paper. First of all, we expand the histograms of oriented gradients features from single-size to variable-size which can capture local and global feature of pedestrian automatically. We call theses feature as the "spatial histograms of oriented gradients". Secondly, we employ histogram similarity and Fisher criterion to measure discriminability of features and select some discriminative features to identify the pedestrian. SVM classifier is constructed to train the selected features from target and surrounding background. The proposed algorithm is tested on some public database. Experimental results show that the proposed approach is efficient and rapid in pedestrian detection.
In this paper, we study the global robust synchronization problem of the controlled Duffing system and the Van der Pol oscillator. By employing the internal model approach, we first show that the problem can be conver...
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In this paper, we study the global robust synchronization problem of the controlled Duffing system and the Van der Pol oscillator. By employing the internal model approach, we first show that the problem can be converted into a global robust stabilization problem of a time-varying nonlinear system in lower triangular form. Then we show that the global stabilization problem of the lower triangular system is solvable, thus leading to the solution of the global robust synchronization problem.
Segmentation, feature extraction and classification of signal components belong to very common problems in various engineering, economical and biomedical applications. The paper is devoted to the use of discrete wavel...
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Segmentation, feature extraction and classification of signal components belong to very common problems in various engineering, economical and biomedical applications. The paper is devoted to the use of discrete wavelet transform (DWT) both for signal preprocessing and signal segments feature extraction as an alternative to the commonly used discrete Fourier transform (DFT). Feature vectors belonging to separate signal segments are then classified by a competitive neural network as one of methods of cluster analysis and processing. The paper provides a comparison of classification results using different methods of feature extraction most appropriate for EEG signal components detection. Problems of multichannel segmentation are mentioned in this connection as well.
This paper elaborates the present stage predictable direction of future development of Sine Wave Calculator (SWC), a simple method for signal analysis in time domain that provides accuracy comparable to the best class...
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This paper elaborates the present stage predictable direction of future development of Sine Wave Calculator (SWC), a simple method for signal analysis in time domain that provides accuracy comparable to the best classical methods (relative errors about few times 10-6). The main SWC advantages are extreme simplicity, possibility of selection of samples and straightforward calculations, which makes it preferable solution for quick implementation. The main shortage is still unknown mathematical analysis of errors, which are probably unequal for different signal parameters.
Observations of the long-term geoelectric potential (LTGP) difference are presented in this paper. The data have been collected during a three-year (2004-2006) investigating period. Moreover, this paper constitutes a ...
This paper deals with an analysis of applicability, capabilities, benefits and pitfalls of using a virtual potential field approach to autonomously planning trajectories in non-communicating autonomous underwater vehi...
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