A unified framework for the identification of a general class of multivariable nonlinear block‐structured systems

2021 ◽  
Author(s):  
Vito Cerone ◽  
Valentino Razza ◽  
Diego Regruto
Keyword(s):  
General Class ◽  
Unified Framework ◽  
Structured Systems ◽  
Block Structured

scholarly journals A Hierarchical Co-operative Exception Handling Mechanism

1986 ◽  
Vol 15 (204) ◽  
Author(s):  
Jørgen Lindskov Knudsen
Keyword(s):  
Data Structures ◽  
Exception Handling ◽  
Layered System ◽  
Layered Systems ◽  
Abstract Machine ◽  
Structured Systems ◽  
Structured System ◽  
Handling Mechanism ◽  
Special Case ◽  
Block Structured

<p>One of the most dominant philosophies within programming disciplines is the philosophy of layered systems. In a layered system (or hierarchical system) the layers are thought of as each implementing an abstract machine on top of the lower layers. Such an abstract machine in turn implements utilities (e.g. data-structures and operations) to be used at higher layers.</p><p>This paper will focus on exception handling in block-structured systems (as a special case of layered systems). It will be argued that none of the existing programming language proposals for exception handling support secure and well-behaved termination of activities in a block-structured system. Moreover, it is argued that certain termination strategies within block-structured systems cannot be implemented using the existing proposals. As a result of this discussion and as a solution to the problems, a hierarchical, co-operative exception handling mechanism is proposed.</p>

Better Exception-Handling in Block-Structured Systems

IEEE Software ◽  
1987 ◽  
Vol 4 (3) ◽  
pp. 40-49 ◽  
Author(s):  
J.L. Knudsen
Keyword(s):  
Exception Handling ◽  
Structured Systems ◽  
Block Structured

scholarly journals A Unified Framework for Solving a General Class of Conditional and Robust Set-Membership Estimation Problems

2014 ◽  
Vol 59 (11) ◽  
pp. 2897-2909 ◽  
Author(s):  
Vito Cerone ◽  
Jean-Bernard Lasserre ◽  
Dario Piga ◽  
Diego Regruto
Keyword(s):  
General Class ◽  
Unified Framework ◽  
Set Membership ◽  
Estimation Problems

scholarly journals Direct linearizing transform for three-dimensional discrete integrable systems: the lattice AKP, BKP and CKP equations

2017 ◽  
Vol 473 (2203) ◽  
pp. 20160915 ◽  
Author(s):  
Wei Fu ◽  
Frank W. Nijhoff
Keyword(s):  
Integrable Systems ◽  
General Class ◽  
Solution Structure ◽  
Three Dimensional ◽  
Integral Transforms ◽  
Unified Framework ◽  
Discrete Integrable Systems

A unified framework is presented for the solution structure of three-dimensional discrete integrable systems, including the lattice AKP, BKP and CKP equations. This is done through the so-called direct linearizing transform, which establishes a general class of integral transforms between solutions. As a particular application, novel soliton-type solutions for the lattice CKP equation are obtained.

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

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