Search results for "programming."

showing 10 items of 3035 documents

Stabilization of a class of slowly switched positive linear systems: State-feedback control

2012

The main goal of this paper is to investigate the stabilization problem for a class of switched positive linear systems (SPLS) with average dwell time (ADT) switching in continuous-time context. State-feedback controllers and the corresponding switching law with ADT property are designed, which stabilize the closed-loop systems while keeping the states nonnegative. The proposed conditions, formulated as linear matrix inequalities, can be directly used for controller synthesis and switching designing. Finally, a numerical example is given to demonstrate the validity of the obtained results.

Dwell timeClass (set theory)Property (programming)Control theoryLinear systemContext (language use)State (functional analysis)Stability (probability)Mathematics2012 American Control Conference (ACC)
researchProduct

Impulsively-controlled systems and reverse dwell time: A linear programming approach

2015

We present a receding horizon algorithm that converges to the exact solution in polynomial time for a class of optimal impulse control problems with uniformly distributed impulse instants and governed by so-called reverse dwell time conditions. The cost has two separate terms, one depending on time and the second monotonically decreasing on the state norm. The obtained results have both theoretical and practical relevance. From a theoretical perspective we prove certain geometrical properties of the discrete set of feasible solutions. From a practical standpoint, such properties reduce the computational burden and speed up the search for the optimum thus making the algorithm suitable for th…

Dwell timeMathematical optimizationUnimodular matrixLinear programmingControl and Systems EngineeringHybrid systemNorm (mathematics)Monotonic functionImpulse (physics)Time complexityAnalysisComputer Science ApplicationsMathematicsNonlinear Analysis: Hybrid Systems
researchProduct

Quantized Dissensus in Networks of Agents subject to Death and Duplication

2012

Dissensus is a modeling framework for networks of dynamic agents in competition for scarce resources. Originally inspired by biological cells behaviors, it fits also marketing, finance and many other application areas. Competition is often unstable in the sense that strong agents, those having access to large resources, gain more and more resources at the expense of weak agents. Thus, strong agents duplicate when reaching a critical amount of resources, whereas weak agents die when loosing all their resources. To capture all these phenomena we introduce systems with a discrete time gossip and unstable state dynamics interrupted by discrete events affecting the network topology. Invariancy o…

Dynamic ProgrammingConsensus ProtocolsComputer sciencemedia_common.quotation_subjectDistributed computingSubject (philosophy)Dynamical Systems (math.DS)Network topologyConsensus protocolScarcityCompetition (economics)Settore ING-INF/04 - AutomaticaGossipFOS: MathematicsElectrical and Electronic EngineeringMathematics - Dynamical SystemsMathematics - Optimization and Controlmedia_commonConsensus Protocols; Quantized Control; Dynamic Programming; Network based marketing; Dynamic Pie Diagram.Dynamic Pie Diagramquantized controlComputer Science ApplicationsConsensus protocolsConsensus protocols; network based marketing; quantized controlDiscrete time and continuous timeControl and Systems Engineeringnetwork based marketingOptimization and Control (math.OC)90C3993Dxx34K2034a38Settore MAT/09 - Ricerca Operativa
researchProduct

GAIML: A New Language for Verbal and Graphical Interaction in Chatbots

2008

Natural and intuitive interaction between users and complex systems is a crucial research topic in human-computer interaction. A major direction is the definition and implementation of systems with natural language understanding capabilities. The interaction in natural language is often performed by means of systems called chatbots. A chatbot is a conversational agent with a proper knowledge base able to interact with users. Chatbots appearance can be very sophisticated with 3D avatars and speech processing modules. However the interaction between the system and the user is only performed through textual areas for inputs and replies. An interaction able to add to natural language also graph…

Dynamic interface generation chatbot pattern definition GAIMLSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer Networks and CommunicationsComputer scienceInterface (Java)Natural language understandingTK5101-6720AIMLcomputer.software_genreChatbotComputer Science ApplicationsConstructed languageWorld Wide WebHuman–computer interactionTelecommunicationDialog systemUser interfacecomputerNatural languagecomputer.programming_languageMobile Information Systems
researchProduct

Optimal Usage of Multiple Network Connections

2008

In the future mobile networks, a mobile terminal is able to select the best suitable network for each data transmission. The selection of a network connection to be used has been under a lot of study. In this paper, we consider a more extensive case in which we do not select a network connection but use several network connections simultaneously to transfer data. When data is transferred using multiple network connections, a network connection has to be selected for each component of the data. We have modelled this problem as a multiobjective optimization problem and developed a heuristic to solve the problem fast in a static network environment. In this paper, we discuss solving the proble…

Dynamic network analysisHeuristic (computer science)Computer scienceDistributed computingInteger programminglangaton tiedonsiirtoTerminal (electronics)optimointiTransfer (computing)Component (UML)langaton viestintäNetwork conditionsSelection (genetic algorithm)Data transmission
researchProduct

Inferring slowly-changing dynamic gene-regulatory networks

2015

Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experi…

Dynamic network analysisL1 penalized inferenceComputer scienceT-LymphocytesGene regulatory networkgene regulatory networkMachine learningcomputer.software_genreBiochemistrygene-regulatory networksStructural Biologygraphical modelscomputer simulationT lymphocyteHumansGene Regulatory NetworkshumanGraphical modelMolecular Biologylymphocyte activationClass (computer programming)Models Statisticalalgorithmbusiness.industryResearchApplied Mathematicsstatistical modelStatistical modelComplex networkQuantitative Biology::GenomicsComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONConditional independencemicroarray analysisComputingMethodologies_GENERALArtificial intelligencebusinessmetabolismRandom variablecomputerAlgorithmsBMC Bioinformatics
researchProduct

Swing options in commodity markets: a multidimensional Lévy diffusion model

2013

Author's version of an article in the journal: Mathematical Methods of Operations Research. Also available from the publisher at: http://dx.doi.org/10.1007/s00186-013-0452-7 We study valuation of swing options on commodity markets when the commodity prices are driven by multiple factors. The factors are modeled as diffusion processes driven by a multidimensional Lévy process. We set up a valuation model in terms of a dynamic programming problem where the option can be exercised continuously in time. Here, the number of swing rights is given by a total volume constraint. We analyze some general properties of the model and study the solution by analyzing the associated HJB-equation. Furthermo…

Dynamic programming problemHJB-equationComputer scienceGeneral MathematicsFinite difference methodManagement Science and Operations ResearchSwingSwing optionFinite difference methodMulti-factor modelLévy diffusionVDP::Social science: 200::Economics: 210::Economics: 212Mathematical economicsFlexible load contractSoftwareMathematical Methods of Operations Research
researchProduct

Parameter Matching Analysis of Hydraulic Hybrid Excavators Based on Dynamic Programming Algorithm

2013

Published version of an article in the journal: Journal of Applied Mathematics. Also available from the publisher at: http://dx.doi.org/10.1155/2013/615608 Open Access In order to meet the energy saving requirement of the excavator, hybrid excavators are becoming the hot spot for researchers. The initial problem is to match the parameter of each component, because the system is tending to be more complicated due to the introduction of the accumulator. In this paper, firstly, a new architecture is presented which is hydraulic hybrid excavator based on common pressure rail combined switched function (HHES). Secondly, the general principle of dynamic programming algorithm (DPA) is explained. T…

Dynamic programmingAccumulator (energy)ExcavatorOptimal matchingArticle SubjectControl theoryComputer scienceApplied Mathematicslcsh:Mathematicslcsh:QA1-939VDP::Teknologi: 500::Maskinfag: 570::Maskinteknisk energi- og miljøteknologi: 573Algorithm
researchProduct

Realizing Undelayed N-step TD prediction with neural networks

2010

There exist various techniques to extend reinforcement learning algorithms, e.g., eligibility traces and planning. In this paper, an approach is proposed, which combines several extension techniques, such as using eligibility-like traces, using approximators as value functions and exploiting the model of the environment. The obtained method, ‘Undelayed n-step TD prediction’ (TD-P), has produced competitive results when put in conditions of not fully observable environment.

Dynamic programmingArtificial neural networkComputer sciencebusiness.industryValue (computer science)Reinforcement learningObservableExtension (predicate logic)Artificial intelligencebusinessMelecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference
researchProduct

Longest Common Subsequence from Fragments via Sparse Dynamic Programming

1998

Sparse Dynamic Programming has emerged as an essential tool for the design of efficient algorithms for optimization problems coming from such diverse areas as Computer Science, Computational Biology and Speech Recognition [7,11,15]. We provide a new Sparse Dynamic Programming technique that extends the Hunt-Szymanski [2,9,8] paradigm for the computation of the Longest Common Subsequence (LCS) and apply it to solve the LCS from Fragments problem: given a pair of strings X and Y (of length n and m, resp.) and a set M of matching substrings of X and Y, find the longest common subsequence based only on the symbol correspondences induced by the substrings. This problem arises in an application t…

Dynamic programmingCombinatoricsSet (abstract data type)Longest common subsequence problemOptimization problemMatching (graph theory)Combinatorial optimizationData structureSubstringMathematics
researchProduct