In this paper, a vector generalization of weighted median optimization approaches is provided. The proposed optimized weighted vector median filters utilize the relationship between standard median filter and vector m...
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A behavior-based control and learning architecture is proposed, where reinforcement learning is applied to learn proper associations between stimulus and response by using two types of memory called as short Term Memo...
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ISBN:
(纸本)0780377362
A behavior-based control and learning architecture is proposed, where reinforcement learning is applied to learn proper associations between stimulus and response by using two types of memory called as short Term Memory and Long Term Memory. In particular, to cope with delayed-reward problem, a knowledge-propagation (KP) method is proposed, where well-designed or well-trained S-R(stimulus-response) associations for low-level sensors are utilized to learn new S-R associations for high-level sensors, in case that those S-R associations require same objective such as obstacle avoidance. To show the validity of our proposed KP method, comparative experiments are performed for the cases that:(1) only a delayed reward is used, (2) some of S-R pairs are preprogrammed, (3) immediate reward is possible, and (4) our KP method is applied.
In this paper we give a sufficient condition (in terms of an LMI) for the well-posedness of a feedback interconnection between a linear system and an incrementally sector bounded static nonlinearity. In particular, we...
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In this paper we give a sufficient condition (in terms of an LMI) for the well-posedness of a feedback interconnection between a linear system and an incrementally sector bounded static nonlinearity. In particular, we prove the global invertibility of the algebraic constraint arising from the feedback interconnection and prove a suitable Lipschitz bound for the arising global inverse function. We also comment on the useful ramifications of the proposed condition on LMI- based anti-windup synthesis methods recently proposed in the literature, wherein possible numerical problems arising from solutions which are "almost" non well-posed are ruled out by enforcing a suitable Lipschitz constant on the inverse function.
In this paper a model based nonlinear controller for a Gas Metal Arc Welding (GMAW) system is designed. The controller uses nonlinear state feedback to exactly linearize and decouple the GMAW system. The linearized sy...
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In this paper a model based nonlinear controller for a Gas Metal Arc Welding (GMAW) system is designed. The controller uses nonlinear state feedback to exactly linearize and decouple the GMAW system. The linearized system is then controlled using model reference sliding mode controllers. The effect of parameter uncertainty over the closed loop system performance is investigated and simulation results show the effectiveness of the proposed controller.
We now apply the model predictive control (MPC) of speed limits that we have presented in previous publications to a calibrated METANET model of a 19 km stretch of the real-world freeway A1 in The Netherlands. This fr...
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We now apply the model predictive control (MPC) of speed limits that we have presented in previous publications to a calibrated METANET model of a 19 km stretch of the real-world freeway A1 in The Netherlands. This freeway regularly suffers from shock waves originating mainly from on-ramps, and speed limits are now used to suppress these shock waves. First, we calibrate and validate the extended METANET model with data from the A1 freeway, and we use the Delft OD method to estimate the origin-destination patterns that are needed for the simulation of the destination oriented traffic. Next, we verify from data whether the necessary conditions for applying speed limits against shock waves are satisfied. We show that the MPC controller performs well even under the assumption that the traffic demand is not known on the on-ramps and is known for only a few kilometers upstream and downstream of the controlled stretch. This approach results in an improvement of the total time spent in the network with about 15%.
In this paper, a new adaptive multichannel filter for the detection and removal of impulsive noise, bit errors and outliers in digital color images is provided. The proposed nonlinear filter takes the advantages of th...
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We now apply the model predictive control (MPC) of speed limits that we have presented in previous publications to a calibrated METANET model of a 19 km stretch of the real-world freeway A1 in The Netherlands. This fr...
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We provide new adaptive multichannel filtering schemes for the detection and removal of impulsive noise, bit errors and outliers in digital color images. The proposed nonlinear filter is based on the generalized multi...
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We provide new adaptive multichannel filtering schemes for the detection and removal of impulsive noise, bit errors and outliers in digital color images. The proposed nonlinear filter is based on the generalized multichannel concept of the local entropy contrast and the robust order-statistics theory. The proposed entropy based directional distance filter is computationally attractive, robust for a wide range of the impulsive noise corruption and significantly improves the signal-detail preservation capability of the standard multichannel filters outputting the lowest ranked vector as the output sample.
In this paper we provide a new filtering scheme for the detection and the removal of impulsive noise in digital color images. The proposed adaptive nonlinear vector filters take the advantages of the robust order-stat...
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In this paper we provide a new filtering scheme for the detection and the removal of impulsive noise in digital color images. The proposed adaptive nonlinear vector filters take the advantages of the robust order-statistic theory, generalized directional distance filter and standard sigma filter concept. The principles of the design are explained in detail. Simulation studies indicate that the proposed method is computationally attractive and is able to achieve excellent balance between the image-detail preservation and the noise attenuation.
In this paper, a vector generalization of weighted median optimization approaches is provided. The proposed optimized weighted vector median filters utilize the relationship between standard median filter and vector m...
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In this paper, a vector generalization of weighted median optimization approaches is provided. The proposed optimized weighted vector median filters utilize the relationship between standard median filter and vector median filter and also take the advantage of the generalized adaptive optimization algorithms initially developed for weighted median filters.
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