In this paper, we study marginal problems for a class of binary pairwise Gibbs random fields (BPW-GRFs). Given a BPW-GRF associated with a family of binary positive pairwise potentials, finding the exact marginal for ...
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In this paper, we study marginal problems for a class of binary pairwise Gibbs random fields (BPW-GRFs). Given a BPW-GRF associated with a family of binary positive pairwise potentials, finding the exact marginal for each random variable is typically an NP-hard problem. In this paper, we develop upper and lower bounds of the true marginals in BPW-GRFs. Our bounds can be easily computed via an iteration on appropriate trees that are constructed from the corresponding BPW-GRF graphs. We prove that these marginal bounds outperform existing bounds. We also show via simulations that this improvement is significant on graphs with weak potentials.
In this paper, we discuss in time domain the convergence of the iterative process for fractional-order nonlinear systems. The PD~(alpha)-type iterative learning updating laws are considered. Most of the classical frac...
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In this paper, we discuss in time domain the convergence of the iterative process for fractional-order nonlinear systems. The PD~(alpha)-type iterative learning updating laws are considered. Most of the classical fractional-order cases for linear or nonlinear systems fall into the scheme of this paper. A number of numerical simulations are illustrated to validate the concepts.
The Discrete Cosine Transform (DCT) is one of the most widely used techniques for image compression. Several algorithms are proposed to implement the DCT-2D. The scaled SDCT algorithm is an optimization of the DCT-1D,...
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The Discrete Cosine Transform (DCT) is one of the most widely used techniques for image compression. Several algorithms are proposed to implement the DCT-2D. The scaled SDCT algorithm is an optimization of the DCT-1D, which consists in gathering all the multiplications at the end. In this paper, in addition to the hardware implementation on an FPGA, an extended optimization has been performed by merging the multiplications in the quantization block without having an impact on the image quality. Tests using MATLAB environment have shown that our proposed approach produces images with quality comparable to the ones obtained using the JPEG standard. FPGA-based implementations of this proposed approach and the Loeffler's algorithm are proposed and compared in this paper using an Altera Startix FPGA family with the synthesis and implementation tool Quartus II. Results show that our approach outperforms the well known Loeffler's algorithm in terms of processing-speed and resources used.
Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical mo...
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Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical model of the PMSM is necessary. A model with nonlinear dynamics and a Fourier approach for the ripples is used as a mathematical description. Through comparisons between measured data and simulated data it is shown that the model assumptions are valid. The adaptive algorithm is implemented as an add-on controller to the already existing control system which consists of a feedforward part and a basis controller. The challenge is that the closed loop system has a resonant frequency and the algorithm should have the same performance for all frequencies. Experimental results show the performance and convergence of the adaptive algorithm at constant and non constant velocity.
The unit quaternion is a pervasive representation of rigid-body attitude used for the design and analysis of feedback control laws. Quaternion-based feedback control laws that are inconsistent (i.e. do not have a uniq...
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The unit quaternion is a pervasive representation of rigid-body attitude used for the design and analysis of feedback control laws. Quaternion-based feedback control laws that are inconsistent (i.e. do not have a unique value for a given attitude) require an additional mechanism that lifts a continuous attitude trajectory to the unit quaternion space. Lifting mechanisms that are memoryless, for example, selecting the quaternion having positive scalar component, have a limited domain where they remain injective and, when used globally, introduce discontinuities into the closed-loop system. We show that such discontinuities can be exploited by an arbitrarily small measurement disturbance to stabilize attitudes far from the desired attitude and destroy "global" attractivity properties.
The group technology is the bottleneck of large-scale lithium battery storage energy system. The estimate of residual capacity of SOC (state of charge) is an important method to realize large-scale group technology an...
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The group technology is the bottleneck of large-scale lithium battery storage energy system. The estimate of residual capacity of SOC (state of charge) is an important method to realize large-scale group technology and the resistance of battery is a major index evaluating SOC. Wavelet analysis theory is used for equivalent circuit model of lithium battery aiming at the characteristics of output signal with gaussian white noise when the lithium battery is discharged or charged. The output of current signal and voltage signals in lithium battery are decomposed into multi-scale functions by choosing the optimum wavelet base function to realize filter processing of noise signals, and then the filtered signals be reconstructed to obtain more accurate battery resistance. Compared with the traditional filtering method (LMS adaptive method), wavelet filtering method provided in this paper can effectively remove interference signals and realize accurately estimate of SOC for lithium battery in large-scale battery storage energy system with certain practical significance for group technology.
This paper presents a vision-tracking for mobile robots, which tracks a moving target based on robot motion and stereo vision information. The proposed system controls pan and tilt actuators attached to a stereo camer...
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This paper presents a vision-tracking for mobile robots, which tracks a moving target based on robot motion and stereo vision information. The proposed system controls pan and tilt actuators attached to a stereo camera, using the data from a gyroscope, robot wheel encoders, pan and tilt actuator encoders, and the stereo camera. Using this proposed system, the stereo camera always faces the moving target. The developed system calculates the angles of the pan and tilt actuators by estimating the relative position of the target with respect to the position of the robot. The developed system estimates the target position using the robot motion information and the stereo vision information. The movement of the robot is modeled as the transformation of the frame, which consists of a rotation and a translation. The developed system calculates the rotation using 3-axis gyroscope data and the translation using robot wheel encoder data. The proposed system measures the position of the target relative to the robot, combining the encoder data of pan and tilt actuators and the disparity map of the stereo vision. The inevitable mismatch of the data, which occurs from the asynchrony of the multiple sensors, is prevented by the proposed system, which compensates for the communication latency and the computation time. The experimental results show that the developed system achieves excellent tracking performance in several motion scenarios, including combinations of straights and curves and climbing of slopes.
Functional connectivity can be evaluated by temporal correlation between spatial neurophysiologic events or correlation between neural activities of brain regions. Unlike anatomical connectivity which represents physi...
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Functional connectivity can be evaluated by temporal correlation between spatial neurophysiologic events or correlation between neural activities of brain regions. Unlike anatomical connectivity which represents physical connections between two brain regions, functional connectivity investigates interactions between brain regions. In this study, we implemented and evaluated Probabilistic Independent Component Analysis (PICA) and generalized Canonical Correlation Analysis (gCCA) on resting state data of healthy subjects and subjects with ADHD disorders from NITRC database. This was done to detect brain functional connectivity and compare the results in normal and diseased subjects. In addition, speed of the methods was compared. Our study shows that relative to PICA, gCCA has higher precision and accuracy and lower computational complexity and run time in addition to capability of extracting more reproducible statistical maps in both control and ADHD subjects.
The notion of synergistic potential functions has been introduced recently in the literature and has been used as the basis for the design of hybrid feedback laws that achieve global asymptotic stabilization of a poin...
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The notion of synergistic potential functions has been introduced recently in the literature and has been used as the basis for the design of hybrid feedback laws that achieve global asymptotic stabilization of a point on a compact manifold (without boundary) such as S~(1), S~(2), and SO(3). Here, synergistic potential functions are generalized--to synergistic Lyapunov functions--and are shown to be amenable to backstepping. In particular, if an affine control system admits a (weak) synergistic Lyapunov function and feedback pair then the system with an integrator added at the input also admits a synergistic Lyapunov and feedback pair. This fact enables "smoothing" hybrid feedbacks, or implementing them through a chain of integrators. In this way, hybrid control designed at a kinematic level can be redesigned for control through forces, torques, or even the derivative of these quantities. We demonstrate the backstepping procedure for attitude stabilization of a rigid body using a quaternion parametrization.
In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatm...
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