This paper introduced a novel high performance algorithm and VLSI architectures for achieving bit plane coding (BPC) in word level sequential and parallel mode. The proposed BPC algorithm adopts the techniques of co...
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This paper introduced a novel high performance algorithm and VLSI architectures for achieving bit plane coding (BPC) in word level sequential and parallel mode. The proposed BPC algorithm adopts the techniques of coding pass prediction and parallel & pipeline to reduce the number of accessing memory and to increase the ability of concurrently processing of the system, where all the coefficient bits of a code block could be coded by only one scan. A new parallel bit plane architecture (PA) was proposed to achieve word-level sequential coding. Moreover, an efficient high-speed architecture (HA) was presented to achieve multi-word parallel coding. Compared to the state of the art, the proposed PA could reduce the hardware cost more efficiently, though the throughput retains one coefficient coded per clock. While the proposed HA could perform coding for 4 coefficients belonging to a stripe column at one intra-clock cycle, so that coding for an NxN code-block could be completed in approximate N2/4 intra-clock cycles. Theoretical analysis and experimental results demonstrate that the proposed designs have high throughput rate with good performance in terms of speedup to cost, which can be good alternatives for low power applications.
Many researchers have applied clustering to handle semi-supervised classification of data streams with concept ***,the generalization ability for each specific concept cannot be steadily improved,and the concept drift...
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Many researchers have applied clustering to handle semi-supervised classification of data streams with concept ***,the generalization ability for each specific concept cannot be steadily improved,and the concept drift detection method without considering the local structural information of data cannot accurately detect concept *** paper proposes to solve these problems by BIRCH(Balanced Iterative Reducing and Clustering Using Hierarchies)ensemble and local structure *** local structure mapping strategy is utilized to compute local similarity around each sample and combined with semi-supervised Bayesian method to perform concept *** a recurrent concept is detected,a historical BIRCH ensemble classifier is selected to be incrementally updated;otherwise a new BIRCH ensemble classifier is constructed and added into the classifier *** extensive experiments on several synthetic and real datasets demonstrate the advantage of the proposed algorithm.
In the last decades,as a typical nonlinear system,active magnetic bearings(AMB) system has been widely applied in manufacturing systems.A sliding mode control(SMC) scheme for the AMB system is proposed with the distur...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
In the last decades,as a typical nonlinear system,active magnetic bearings(AMB) system has been widely applied in manufacturing systems.A sliding mode control(SMC) scheme for the AMB system is proposed with the disturbance observation of the linear extended state observer(LESO) in this *** chattering of the AMB system has been reduced by LESO-SMC by at least 60%.Sufficient BIBO(bounded input-bounded output) stability conditions of the closed-loop AMB system governed by the proposed LESO-SMC are derived by Lyapunov ***,experiments are conducted to verify the effectiveness and superiority of the proposed LESO-SMC than conventional SMC.
Due to its high degree of customization, DNA origami provides a versatile platform with which to engineer nanoscale structures and devices. Reconfigurable nanodevices driven by DNA strand displacement accomplish the t...
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Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired by the way neurons communicate by means of electrical impulses or spikes. SN P systems with astrocytes ...
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This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. Thi...
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作者:
Bian, YuanLiu, MinYi, YunqiWang, XuepingMa, YunfengWang, YaonanHunan University
National Engineering Research Center of Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan Changsha China Hunan Normal University
Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Changsha China
Deep learning based person re-identification (re-id) models have been widely employed in surveillance systems. Recent studies have demonstrated that black-box single-modality and cross-modality re-id models are vulner...
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Dear Editor, This letter investigates the prescribed-time stabilization of linear singularly perturbed systems. Due to the numerical issues caused by the small perturbation parameter, the off-the-shelf control design ...
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Dear Editor, This letter investigates the prescribed-time stabilization of linear singularly perturbed systems. Due to the numerical issues caused by the small perturbation parameter, the off-the-shelf control design techniques for the prescribed-time stabilization of regular linear systems are typically not suitable here. To solve the problem, the decoupling transformation techniques for time-varying singularly perturbed systems are combined with linear time-varying high gain feedback design techniques.
Nature or natural systems are a rich source for the inspiration of new computational paradigms and techniques. Examples of nature inspired computational paradigms include evolutionary algorithms, artificial neural net...
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The fault detection task in lithium-ion battery management system (BMS) is critical to the safety and reliability of rechargeable and hybrid electric vehicles. To explicitly account for inevitable errors of battery mo...
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