Tuning a PI controller can be quite cumbersome for the non-expert as the closed-loop control system has to meet various requirements while the influence and interaction of the two degrees of freedom are not always cle...
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System identification with regularization methods has attracted increasing attention recently and is a complement to the current standard maximum likelihood/prediction error method. In this paper, we focus on the kern...
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ISBN:
(纸本)9781479978878
System identification with regularization methods has attracted increasing attention recently and is a complement to the current standard maximum likelihood/prediction error method. In this paper, we focus on the kernel-based regularization method and give a spectral analysis of the so-called diagonal correlated (DC) kernel, one family of kernel structures that has been proven useful for linear time-invariant system identification. In particular, using the theory of Bessel functions, we derive the eigenvalues and corresponding eigenfunctions of the DC kernel. Accordingly, we derive the Karhunen-Loeve expansion of the stochastic process whose covariance function is the DC kernel.
This paper presents a method for the estimation of city environmental noise. In this paper is applied the least square method to get the curve that approximates best the samples. Also, it is estimated the environmenta...
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This paper presents a method for the estimation of city environmental noise. In this paper is applied the least square method to get the curve that approximates best the samples. Also, it is estimated the environmental noise model using the System Identification Tool from Matlab. The model structure is chosen, next parameters are estimated and then the model is validated.
In this paper a new Novelty Detection framework is presented, which is created by taking advantage of the Fuzzy Entropy property of Fuzzy Logic systems. The framework’s aim is to create a linguistic-based feedback me...
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In this paper, a novel visual activity recognition algorithm based on the depth contour image and nearest neighbor (NN) classifier is presented, where the depth contour image is acquired by solving algebraic matrix eq...
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In this paper, a novel visual activity recognition algorithm based on the depth contour image and nearest neighbor (NN) classifier is presented, where the depth contour image is acquired by solving algebraic matrix equations in terms of the newly-defined Spatial Motion Accumulative Image (SMAI) and Temporal Motion Accumulative Image (TMAI). More precisely, firstly, SMAI and TMAI are defined based on the binary image sequences of action video segments; secondly, the pixel values in SMAI are re-evaluated by the average traveling time for (virtual) free particles from the corresponding pixel positions to the contour border with the so-called TMAI-determined speed, which leads to the proposed depth contour image; thirdly, the principal component analysis (PCA) is applied to extract the feature vectors from the depth contour image to characterize human actions; finally, the NN classifier is used to recognize the human actions. Experimental results on the open Weizmann activity database confirm the expected recognition performance of the proposed algorithm.
In this chapter, we present in an unified manner the latest developments on inverse optimality problem for continuous piecewise affine (PWA) functions. A particular attention is given to convex liftings as a cornersto...
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We consider the problem of estimating the occupancy level in buildings using indirect information such as CO_2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a devi...
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ISBN:
(纸本)9781479978878
We consider the problem of estimating the occupancy level in buildings using indirect information such as CO_2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO_2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO_2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation.
This paper proposes a new fault-tolerant control (FTC) method for discrete-time linear parameter varying (LPV) systems using a reconfiguration block. The basic idea of the method is to achieve the FTC goal without red...
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Psychological studies have often suggested that internal models of the body and its structure are used to process sensory inputs such as proprioception from muscles and joints. Within robotics, there is often a need t...
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Psychological studies have often suggested that internal models of the body and its structure are used to process sensory inputs such as proprioception from muscles and joints. Within robotics, there is often a need to have an internal representation of the body, integrating the multi-modal and multi-dimensional spaces in which it operates. Here we propose a body model in the form of a series of distributed spatial maps, that have not been purpose designed but have emerged through our experiments on developmental stages using a minimalist content-neutral approach. The result is an integrated series of 2D maps storing correlations and contingencies across modalities, which has some resonances with the structures used in the brain for sensorimotor coordination.
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