This paper addresses the problem of circuit design and global exponential stabilization of memristive neural networks with time-varying delays and general activation functions. Based on the Lyapunov-Krasovskii functio...
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This paper addresses the problem of circuit design and global exponential stabilization of memristive neural networks with time-varying delays and general activation functions. Based on the Lyapunov-Krasovskii functional method and free weighting matrix technique, a delay-dependent criteria for the global exponential stability and stabilization of memristive neural networks are derived in form of linear matrix inequalities (LMIs). Two numerical examples are elaborated to illustrate the characteristics of the results. It is noteworthy that the traditional assumptions on the boundness of the derivative of the time-varying delays are removed.
This paper established a closed-loop temperature control system for a spatially-separated atomic layer deposition (S-ALD) reactor using generalized predictive control (GPC) algorithm. The GPC-based closed-loop control...
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In this paper, the authors exploit a multispectral image representation to perform more accurate document image binarisation compared to previous color representations. In the first stage, image fusion is employed to ...
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ISBN:
(纸本)9781479957521
In this paper, the authors exploit a multispectral image representation to perform more accurate document image binarisation compared to previous color representations. In the first stage, image fusion is employed to create a "document" and a "background" image. In the second stage, the FastICA algorithm is used to perform background subtraction. In the third stage, a spatial kernel K-harmonic means classifier binarizes the FastICA output. The proposed system outperforms previous efforts on document image binarization.
Automatic target generation process (ATGP) has been found very useful and effective for unsupervised target detection. It performs a sequence of orthogonal subspace projection to extract potential targets of interest....
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ISBN:
(纸本)9781479953141
Automatic target generation process (ATGP) has been found very useful and effective for unsupervised target detection. It performs a sequence of orthogonal subspace projection to extract potential targets of interest. One major issue arises in ATGP is how to terminate the algorithm in the sense that how many targets are required for ATGP to generate before it is terminated. This paper presents a recursive version of ATGP, referred to as recursive ATGP (RATGP) which has two advantages. One is no need of inverting any matrix as ATGP does for finding each target. Most importantly, a stopping rule can be derived for ATGP via RATGP is also developed using the Neyman-Pearosn detection theory to determine how many targets needed to be generated by RATGP before it is terminated.
The need to create useful information from full motion video gathered by drones is a significant motivation for devising methods to approximate human cognitive behaviors. Additionally, the regulatory needs associated ...
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ISBN:
(纸本)9781479957521
The need to create useful information from full motion video gathered by drones is a significant motivation for devising methods to approximate human cognitive behaviors. Additionally, the regulatory needs associated with drone systems has spawned the requirement to be able to confirm, or audit, the activities of such devices. A conditional approach, as compared with a generalized video processing environment, is presented that associates practical and realistic constraints to simplify the problem of finding useful information from video acquired by a drone into something that is tractable and consistent with real-world requirements. A primary contribution of this paper is to introduce the concept of continuous cognition from a theoretical perspective, followed by a practical application derived from an operational system.
Evolutionary membrane computing is an important research direction of membrane computing that aims to explore the complex interactions between membrane computing and evolutionary computation. These disciplines are rec...
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We proposed a composite image guided filtering technique for dynamic PET denoising to enable quantitatively enhanced time frames. The guided filter computes the filtering output by considering the content of a guidanc...
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We proposed a composite image guided filtering technique for dynamic PET denoising to enable quantitatively enhanced time frames. The guided filter computes the filtering output by considering the content of a guidance image, which can be the input image itself or a different image. In this paper, the composite image from the entire time series is considered as the guidance image. Thus, a local linear model is established between the composite image and individual PET time frames. Subsequently, linear ridge regression is exploited to derive an explicit composite image guided filter. For validation, 20 minute FDG PET data from a NEMA NU 4-2008 IQ phantom were acquired in the list-mode format via the Siemens Invoen micro PET, and were subsequently divided and reconstructed into 20 frames. We compared the performances (including visual and quantitative profiles) of the proposed composite image guide filter (CIGF) with a classic Gaussian filter (GF), and a highly constrained back projection (HYPR) filter. The experimental results demonstrated the proposed filter to achieve superior visual and quantitative performance without sacrificing spatial resolution. The proposed CIGF is considerably effective and has great potential to process the data with high noise for dynamic PET scans.
The conventional output regulation problem aims to achieve reference tracking and disturbance rejection while references and disturbances are generated by an autonomous exosystem. When the exosystem is perturbed by an...
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ISBN:
(纸本)9781467360890
The conventional output regulation problem aims to achieve reference tracking and disturbance rejection while references and disturbances are generated by an autonomous exosystem. When the exosystem is perturbed by an external event, a novel robust perturbed output regulation problem is formulated and solved in this paper. The formulation arises from a kind of synchronization problem of multiple agents. Hence, the proposed solution leads to a decentralized control algorithm for synchronization of multiple agents with nonlinear heterogeneous dynamics.
The aim of this paper is to look for efficient algorithms allowing to deal with taking into account the modelization and the cartography of the sea components. Through the analysis carried on the family of Growing Neu...
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