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IEEE Conference on Technologies for Homeland Security

作者： Maurizio Bocca Heikki N. Koivo Faculty of Electronics Communications and Automation Control Engineering Group Helsinki University of Technology Finland

ISBN: (纸本)9781424419777

This paper describes a reconfigurable wireless network of acoustic sensors that records voice signals in different areas of a building and conveys them at the sink node. At their arrival, a light-weight text and language independent algorithm performs the speaker identification task in real time. The end-user can interrupt the normal operation mode of the network and require a signal to a particular node, specifying also sampling frequency and time length of the sampling period. In our simulations, we use a database composed of 200 signals, 60 individuals, and 15 languages. The total execution time is less than 2 seconds. We optimize the parameters of the algorithm, achieving 83% accuracy. We also evaluate its robustness when the sampling frequency and the time length of the signals are reduced. Finally, the power consumption of the operating nodes is analyzed.

关键词： Natural languages Loudspeakers Wireless sensor networks Acoustic sensors Sampling methods Frequency Databases Military computing Signal processing Discrete Fourier transforms

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Automatic Sleep Stage Determination by Multi-Valued Decision Making Based on Conditional Probability with Optimal Parameters

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SICE Journal of control, Measurement, and System Integration 2008年第6期1卷 423-428页

作者： Bei Wang Takenao Sugi Xingyu Wang Masatoshi Nakamura Department of Advanced Systems Control Engineering Graduate School of Science and Engineering Saga UniversityDepartment of Automation School of Information Science and Engineering East China University of Science and Technology Department of Electrical and Electronic Engineering Faculty of Science and Engineering Saga University Department of Automation School of Information Science and Engineering East China University of Science and Technology Department of Advanced Systems Control Engineering Graduate School of Science and Engineering Saga University

Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.

关键词： automatic sleep stage determination visual inspection multi-valued decision making parameter selection conditional probability

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Performance-aware power management in embedded controllers with multiple-voltage processors

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Information Technology Journal 2008年第6期7卷 942-947页

作者： Xia, Feng Liu, Liping Ma, Longhua Sun, Youxian Dong, Jinxiang College of Computer Science and Technology Zhejiang University Hangzhou 310027 China School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China State Key Lab of Industrial Control Technology Zhejiang University Hangzhou 310027 China Faculty of Information Technology Queensland University of Technology Brisbane QLD 4001 Australia

The aim of this research is to minimize the energy dissipation of embedded controllers without jeopardizing the Quality of control (QoC). Taking advantage of the Dynamic Voltage Scaling (DVS) technology, this study develops a performance-aware power management scheme for embedded controllers with processors that allow multiple voltage levels. The periods of control tasks are adapted online with respect to the current QoC, thus facilitating additional energy reduction over standard DVS. To avoid the waste of CPU resources as a result of the discrete voltage levels, a resource reclaiming mechanism is employed to maximize the CPU utilization and also to improve the QoC Simulations are conducted to evaluate the performance of the proposed scheme. Compared with the optimal standard DVS scheme, the proposed scheme is shown to be able to save remarkably more energy while maintaining comparable QoC. © 2008 Asian Network for Scientific Information.

关键词： Real time control

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Object Shape Description Using Haar-Wavelet Functions

Object Shape Description Using Haar-Wavelet Functions

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3rd International Conference on Information and Communication Technologies, vol.2

作者： Adnan Abou Nabout Bernd Tibken Chair of Automatic Control Faculty of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany

Similar to the shape description using Mexican Hat Wavelet functions we present in this paper the derivation of object descriptors using Haar Wavelets. The derivation is based on the continuous wavelet transformation of an angle function using the Haar function as mother wavelet. The angle function which represents a given object shape is derived from the extracted contour polygon by computing the angle differences between the angles at every position on the contour and the angle at the starting point. This angle function is periodical but with 2πoffset and can be normalized in order to be independent of the object's size, it's position and orientation. The angle function depends only on the starting point on the given contour. Moreover, the used angle function doesn't include any singularity which might arise due to object rotations. The derived Wavelet descriptors were used in an agricultural application to recognize weed species. The paper presents in this context some derived results as well as possible solution for the problem of starting point.

关键词： Image Processing Object Recognition Shape Representation Wavelet Transformation Haar Wavelet Descriptors

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The influence of the Cole-Cole model coefficients on the parameters of the recovery voltage phenomena of paper-oil insulation

The influence of the Cole-Cole model coefficients on the par...

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International Conference on Conduction and Breakdown in Dielectric Liquids

作者： S. Wolny M. Zdanowski Faculty of Electrical Engineering Automatic Control and Computer Science Chair of Electrical Power Engineering Opole University of Technology Opole Poland

The paper presents the application of the Cole-Cole model for determining the runs of the return voltage of the paper-oil insulation sample through a computer simulation. Different insulation conditions were simulated through an adequate selection of parameters alpha and tau of the Cole-Cole model. For calculation purposes, a series-parallel substitute scheme, obtained through approximation of a discrete characteristic operator impedance Z a of the model applied, was used. The diagnostics of the simulated insulation condition was based on the analysis of a few selected parameters of the return voltage, obtained from time characteristics.

关键词： Insulation Impedance Mathematical model Approximation methods Voltage measurement Frequency measurement Computational modeling

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Observation of Link Deformations of a Robotic Manipulator with Fiber Bragg Grating Sensors

Observation of Link Deformations of a Robotic Manipulator wi...

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2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Pages 1-476

作者： Rene Franke Frank Hoffmann Torsten Bertram Chair for Control Systems Engineering RST Faculty of Electrical Engineering and Information Technology Technische Universitat Dortmund D-44221 Dortmund Germany

ISBN: (纸本)9781424424948

More advanced robotic applications require high accuracy positioning of the robot manipulator. This paper introduces a novel approach to measure the elastic deformations of robot links in order to improve its pose accuracy. The paper develops a model of the fiber Bragg sensors that locally measure strain. In conjunction with an finite model of the link geometry this information enables the prediction of the arm deformation. The approach opens an avenue for more advanced position control, which considers the elastic link deformations. Both models provide the basis for a systematic analysis and optimization of the spectrometer, signal processing and sensor configuration. An evolutionary algorithm optimizes the sensor locations in order to minimize the predicted deformation error. The proposed scheme is verified experimentally on an industrial manipulator.

关键词： fiber bragg gratings position accuracy optimization industrial manipulator

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New insights into derivative estimation via least squares approximation - theory and application

New insights into derivative estimation via least squares ap...

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2008 American control Conference (ACC), vol.6

作者： Philipp Mai Claus Hillermeier Faculty of Electrical Engineering Institute of Automation and Control Universitat der Bundeswehr München Neubiberg Germany

In this article, we revise a well-known derivative estimation scheme which is based on a least squared error polynomial approximation of a noisy measurement signal. Our contribution is to determine the influence of the estimation parameters onto the covariance matrix and the temporal delay of the estimation result. Also, it is shown that the least squares estimator is statistically optimal in the presence of white gaussian measurement noise. Our ideas are applied to the estimation of derivatives of the first state of Chen's Chaotic Oscillator and to the fault tolerant swing up of the Inverted Pendulum on a Cart.

关键词： Least squares approximation Delay estimation Polynomials Parameter estimation Covariance matrix Noise measurement White noise Gaussian noise State estimation Chaos

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Single-phase optimal Odd PWM problem

Single-phase optimal Odd PWM problem

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Annual Conference of Industrial Electronics Society

作者： Petr Kujan Martin Hromcik Michael Sebek Department of Control Engineering FEEInstitute of Information Theory and Automation of the ASCR Czech Technical University of Prague Center for Applied Cybernetics Faculty of Electrical Engineering Czech Technical University of Prague Department of Control Engineering Faculty of Electrical Engineering Czech Technical University of Prague

Optimal pulse width modulation (PWM) problem is an established method of generating PWM waveforms with low baseband distortion. In this paper we focused on computation of optimal switching angles of a odd PWM waveform for generating general odd symmetric waveforms. We introduce an exact and fast algorithm with the complexity of only O(n log 2 n) arithmetic operations. This algorithm is based on transformation of appropriate trigonometric equations for each harmonics to a polynomial system of equations that is transferred to a special system of sum of powers. The solution of this system is carried out by modification of Newtonpsilas identity via Pade approximation and orthogonal polynomials theory and property of symmetric polynomials. Finally, the optimal switching sequence is obtained by computing the zeros of two orthogonal polynomials in one variable.

关键词： Pulse width modulation Polynomials Baseband Equations Power harmonic filters Chebyshev approximation control engineering Space vector pulse width modulation Pulse generation Pulse width modulation inverters

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Hippocampal-like categorization of object views: A self-organizing learning approach to vision modeling using stochastic grammar inference and associative memory

Hippocampal-like categorization of object views: A self-orga...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Peter Michael Goebel Markus Vincze Bernard Favre-Bulle ACIN Automation & Control Institute Faculty of Electrical Engineering and Information Technology University of Technology Vienna Vienna Austria

The categorization problem in object recognition is the assignment of semantic categories to objects or parts of objects. Here, the best categorization performance provide mammalian brain functions that motivate to partly mimic such a formation for the application to machine learning and automation. Curiosity and experimental willingness support human recognizing and detecting in relation to still unknown objects. In order to learn an understanding of the topology of such objects, objects are observed from a series of different viewpoints. This results in a collection of object views that afterward can be used by cognitive processes. State-of-the-art systems provide learning structures that are subsequently utilized for object recognition and tracking tasks. However, most of these systems aim at very specific goals in restricted domains, and therefore, it remains no room for learning and understanding of object structures. In the work of this paper, we propose a new robot vision model for neural categorization. This is close to our initial idea of mimicking mammalian brain functions for robot vision. We use the combinatorial solution of our cognitive framework with an embedding of a recently presented stochastic n-gram model, supported by a three-dimensional grammar model on a discrete three-dimensional lattice. Furthermore, we use ant colony optimization heuristics for collecting the transition probabilities of the n-gram model. The proposed solution is exemplified by applying the method to several object view series of 69 polytopes generated out of the five platonic solids by truncation; thus, generating images from 32 viewpoints each, yields an object set of 2208 images. These set is further expanded to four sets perturbed by Gaussian-noise with varying sigma = {0, 0.1, 0.5, 1, 2}. Finally, we show results for selected objects and conclude with an outlook on further work.

关键词： Junctions Lattices Stochastic processes Brain modeling Brain models Solid modeling Ant colony optimization

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Subspace identification methods and fMRI analysis

Subspace identification methods and fMRI analysis

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jana Tauchmanova Martin Hromcik Department of Control Engineering Faculty of Electrical Engineering Institute of Information Theory and Automation Czech Technical University Prague Czech Republic Center for Applied Cybernetics Faculty of Electrical Engineering Institute of Information Theory and Automation Czech Technical University Prague Czech Republic

The main goal of this paper is to propose application of modern multidimensional systems identification algorithms of the subspace identification theory in the context of fMRI data analysis. The methods originated in 1990s in the field of process control and identification and yield robust linear model parameter estimates for systems with many inputs, outputs and states. Our ultimate goal is to establish an alternative to the DCM analysis procedure which would eliminate its main drawbacks, namely the need to pre-define the models structure. The paper discusses results based on simulated data provided by the DCM simulator in the SPM toolbox. Several scenarios are presented, with varying amount of noise and number of data samples.

关键词： Data models Functional magnetic resonance imaging Brain modeling Signal to noise ratio Analytical models Mathematical model Process control

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