Image de-noising and restoration represent basic problems in image processing with many different applications including engineering, reconstruction of missing data during their transmission and enhancement of biomedi...
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Image de-noising and restoration represent basic problems in image processing with many different applications including engineering, reconstruction of missing data during their transmission and enhancement of biomedi...
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Image de-noising and restoration represent basic problems in image processing with many different applications including engineering, reconstruction of missing data during their transmission and enhancement of biomedicai structures as well. This problem occurs also in filling-in blocks of missing or corrupted data. The paper presents the use of Wavelet transform in this area including its application for image decomposition and rejection of its components at first. The main part of the paper is devoted (i) to algorithms of restoration of missing image blocks by the search of similar structures of a given image in the Wavelet domain space and (ii) to comparison of this approach with iterated Wavelet interpolation and predictive image modelling. Proposed methods are verified for simulated data and then applied for processing of magnetic resonance images.
In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one o...
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In this paper a non-linear fuzzy autopilot for ship track-keeping is presented. The proposed autopilot has four inputs (actual and desired heading, rate of change of heading and offset from the desired path) and one output (command rudder angle). The track-keeping problem is decomposed into two subtasks: (i) followthe desired heading, and (ii) bring the ship onto the desired path and keep tracking. Internally, the autopilot consists of two autopilots that fulfil these tasks simultaneously. The proposed control scheme has been verified using a non-linear model of a Mariner-class vessel and steering mechanism under the influence of wave and current disturbances. Results presented show how such a control strategy enables improved tracking performance.
Detecting defects in paper pulp manufacturing process’s using a non-touched, effective, on-line and fast method is critical in the paper industry. This work presents a neural network based system for detecting pitch ...
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Traditional approaches to controller designs that guarantee fast compensation of load torque and reference variations result in design iterations and most of the time in poorer response for load torque variations. In ...
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Traditional approaches to controller designs that guarantee fast compensation of load torque and reference variations result in design iterations and most of the time in poorer response for load torque variations. In this paper a reference model for desired drive behavior generation and optimization methods has been applied to achieve controller integral time constant lower than the maximum time constant of the PM brushless DC motor drive. Presented simulation results show that using reference model for desired drive behavior generation, it is possible to determine optimal controller parameters for faster (10 time) and better (2 time) load torque compensation than in the case of traditional design of speed controller parameters. Response due to reference input with constrained overshoot has been achieved using a filter in the servosystem input. Thereby, the proposed method demonstrates the design of a speed controller that is optimal for both load torque and reference variations and its verification with simulation are accomplished for a permanent magnet brushless dc motor drive.
This paper establishes some integral equalities formulated by zeros located in the convergence region of a Laplace transformable function. Using the definition of the Laplace transform, it shows that Laplace transform...
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This paper establishes some integral equalities formulated by zeros located in the convergence region of a Laplace transformable function. Using the definition of the Laplace transform, it shows that Laplace transformable functions have to satisfy the integral equalities in the time-domain, which can be applied to the understanding of the fundamental limitations on the control system represented by the transfer function. In the unity-feedback control scheme, another integral equality is derived on the output response of the system with open-loop poles located in the convergence region of the output function. From these integral equalities, two sufficient conditions related to undershoot and overshoot phenomena in the step response, respectively, are investigated.
In this paper, a new approach is presented for robust filtering of a linear discrete-time signal by applying fictitious noise. Modeling errors, in both the numerator and denominator of the transfer functions, are para...
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ISBN:
(纸本)0780379241
In this paper, a new approach is presented for robust filtering of a linear discrete-time signal by applying fictitious noise. Modeling errors, in both the numerator and denominator of the transfer functions, are parameterized by using random variables with zero mean and known covariance. The robust performance is obtained by minimizing the mean square estimation error over all of the random parameter and noise. To derive a robust estimator, the uncertainties in the model are incorporated into two mutually uncorrelated fictitious noises with zero means. The covariances of the fictitious noises are computed by using two formulas that are presented in this paper. An illustrative example shows the effectiveness of our approach.
One of the basic issues in the navigation of autonomous mobile robots is the obstacle avoidance task that is commonly achieved using a reactive control paradigm where a local mapping from perceived states to actions i...
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One of the basic issues in the navigation of autonomous mobile robots is the obstacle avoidance task that is commonly achieved using a reactive control paradigm where a local mapping from perceived states to actions is acquired. A control strategy with learning capabilities in an unknown environment can be obtained using reinforcement learning where the learning agent is given only sparse reward information. This credit assignment problem includes both temporal and structural aspects. While the temporal credit assignment problem is solved using core elements of the reinforcement learning agent, solution of the structural credit assignment problem requires an appropriate internal state space representation of the environment. In this paper, a discrete coding of the input space using a neural network structure is presented as opposed to the commonly used continuous internal representation. This enables a faster and more efficient convergence of the reinforcement learning process.
In this paper, the design of available bit rate (ABR) congestion control in ATM (asynchronous transfer mode) networks is considered. The goals of congestion control are high link utilization, low cell loss, and low ne...
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In this paper, the design of available bit rate (ABR) congestion control in ATM (asynchronous transfer mode) networks is considered. The goals of congestion control are high link utilization, low cell loss, and low network delay. Various algorithms for congestion control can be found in the literature. Most of them are based on a network model, which is assumed to be known. In this paper a recursive least square (RLS) algorithm for on-line identification of the network model is implemented and combined with a generalized predictive controller (GPC) and with an I-controller based on the Smith predictor. Simulations were carried out to prove the effectiveness of the proposed algorithms.
A laboratory model for experimental investigations of the rubber-asphalt sliding pair has been designed with the purpose of better understanding of dynamic behavior of the friction force in the contact patch between t...
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