To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform (N...
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To preserve the sharp features and details of the synthetic aperture radar (SAR) image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform (NSBT) domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges are detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Ganssian scale mixture (BLS-GSM).
To weaken the degradation phenomenon of digital chaotic systems with finite computing precision, the paper brings forward a varying parameter compensation method (VPCM) on the basis of the Lyapunov number. According t...
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To weaken the degradation phenomenon of digital chaotic systems with finite computing precision, the paper brings forward a varying parameter compensation method (VPCM) on the basis of the Lyapunov number. According to the differential mean-value theorem, the proposed method employs the varying parameter and Lyapunov number to improve the properties of digital chaotic systems with finite computing precision. Results of the experiments demonstrate that: the method prolongs the cycle length greatly, the digital chaotic systems achieve ergodicity in finite precision, and the distribution of digital chaotic sequences (DCSs) approximates that of real chaotic sequences (RCSs). This method can be applied to the fields of chaotic cryptography and broad spectrum communications. (C) 2006 Elsevier Ltd. All rights reserved.
In micromanipulation, the microscope vision servoing can achieve a high performance. In order to avoid the complicated calibration of intrinsic parameter of camera, We apply an improved broyden's method to estimat...
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In this paper the trajectory tracking control of a human arm moving on the sagittal plane is investigated by an interdisciplinary approach with the combination of neural network mapping, evolutionary computation, and ...
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In this paper the trajectory tracking control of a human arm moving on the sagittal plane is investigated by an interdisciplinary approach with the combination of neural network mapping, evolutionary computation, and dynamic system control. The arm in the study is described by a musculoskeletal model with two degrees of freedom and six muscles, and the control signal is applied directly in the muscle space. A new control system structure is proposed to manipulate the complicated nonlinear dynamical arm motion. To design the intelligentcontroller, an evolutionary diagonal recurrent neural network (EDRNN) is integrated with proper performance indices, in which genetic algorithm (GA) and evolutionary program (EP) strategy are effectively integrated with the diagonal recurrent neural network (DRNN). The hybrid GA with EP strategy is applied to optimize the DRNN architecture and an adaptive dynamic back-propagation (ADBP) algorithm with momentum for the multi-input multi-output (MIMO) systems is used to obtain the network weights. The effectiveness of the control scheme is demonstrated through a simulated case study. (c) 2007 Elsevier B.V. All rights reserved.
B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagno...
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ISBN:
(纸本)9781424418145
B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagnosis is mainly qualitative, and often depends on the subjective judgment of technicians and doctors. Therefore, computer-aided feature extraction and quantitative analysis of liver B-scan ultrasonic images will help to improve clinical diagnostic accuracy, repeatability and efficiency, and could provide a measure for severity of hepatic steatosis. This paper proposed a novel method of fatty liver diagnosis based on liver B-mode ultrasonic images using support vector machine (SVM). Fatty liver diagnosis was transformed into a pattern recognition problem of liver ultrasound image features. According to the different characteristics of fatty liver and healthy liver, important image features were extracted and selected to distinguish between the two categories. These features could be represented by near-field light-spot density, near-far-field grayscale ratio, grayscale co-occurrence matrix, and neighborhood gray-tone difference matrix (NGTDM). A SVM classifier was modeled and trained using the clinical ultrasound images of both fatty liver and normal liver. It was then exploited to classify normal and fatty livers, achieving a high recognition rate. The diagnostic results are satisfactorily consistent with those made by doctors. This method could be used for computer-aided diagnosis of fatty liver, and help doctors identify the fatty liver ultrasonic images rapidly, objectively and accurately.
To control the mobile robot with the surrounding information is the essential method to realize the intelligence and automatic moving. The vision information is the most important way to perceive the environment for t...
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ISBN:
(纸本)9781424421138
To control the mobile robot with the surrounding information is the essential method to realize the intelligence and automatic moving. The vision information is the most important way to perceive the environment for the mobile robot. This paper presents an essential camera calibration technique for mobile robot, which is based on Pioneer II experiment platform. The technique includes transformation of coordinates system for vision system, the model and principle of image formations camera distortion calibration. Because of non-linear distortion of camera, algorithm with optimizing operators is presented to improve calibration precision. We verify the validity and feasibility of the algorithm through experiment.
In order to identify multi micro objects, an improved support vector machine algorithm is present, which employs invariant moments based edge extraction to obtain feature attribute and then presents a heuristic attrib...
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Liquid State Machine (LSM) is a newly developed computational model with many interesting properties. It has great advantages of dealing with biologic computing when compared to the traditional computational model. In...
Liquid State Machine (LSM) is a newly developed computational model with many interesting properties. It has great advantages of dealing with biologic computing when compared to the traditional computational model. In this paper, the LSM was used to deal with the direction classification problem of the spike series which were distilled from the neurons in motor cortex of a monkey. In the output layer, a linear regression and back-propagation are employed as the training algorithms. Compare to outcomes of the two algorithms, it is showed that ideal classification results were derived when using BP as the training algorithm.
This paper presents a sliding-mode-based diagonal recurrent cerebellar model articulation controller (SDRCMAC) for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. Sliding mode technology is used to ...
This paper presents a sliding-mode-based diagonal recurrent cerebellar model articulation controller (SDRCMAC) for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. Sliding mode technology is used to reduce the dimension of the control system. Two learning stages are adopted to train the SDRCMAC and to improve the stability of the control system. Lyapunov stability theorem and Barbalat's lemma are adopted to guarantee the asymptotical stability of the system. Performance is illustrated on a two-link robotic control and motor control of the human arm in the sagittal plane.
DNA tile self-assembly has been proved to enable programmable manipulation of biological systems as a tool of molecular computation. It is mainly based on the property that is the spontaneous self-ordering of substruc...
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ISBN:
(纸本)9781424427246
DNA tile self-assembly has been proved to enable programmable manipulation of biological systems as a tool of molecular computation. It is mainly based on the property that is the spontaneous self-ordering of substructure into superstructure driven by annealing of Watson-Crick base-pairing D sequences. We take full advantage of the superiority of DNA tile self-assembly to construct a molecular computing system that implements a solution for the 0-1 planning problem. This algorithm can independently and simultaneously yield the data pool, containing all possible solutions when all basic operation tiles are designed beforehand. Then we can use some advanced bio-chemistry techniques to select the optimization solutions of the 0-1 planning problem. Our work has shown that it is possible to work with an exponential number of components to solve NP-complete problems. The method proposed here also can reduce the number of laboratory steps required for computation so that it can improve the computation speed.
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