Search results for "Memory"

showing 10 items of 2004 documents

Variable Length Memory Chains: Characterization of stationary probability measures

2021

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, turn out to be an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability theory. The question of the existence of stationary probability measures leads us to introduce a key combinatorial structure for words produced by a VLMC: the Longest Internal Suffix. This notion allows us to state a necessary and sufficient condition for a general VLMC to admit a unique invariant probability measure. This condition turns out to get a much simpler form for a subclass of VLMC: the stable VLMC. This natural subclass, unlike the general case, enj…

Statistics and ProbabilityPure mathematicsLongest Internal SuffixStationary distributionMarkov chain60J05 60C05 60G10Probability (math.PR)010102 general mathematics01 natural sciencesMeasure (mathematics)Variable Length Memory Chains010104 statistics & probabilityProbability theoryConvergence of random variablesFOS: MathematicsCountable setState spaceRenewal theory[MATH]Mathematics [math]0101 mathematicsstable context treessemi-Markov chainsMathematics - Probabilitystationary probability measureMathematicsBernoulli
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Non-Markovianity and memory of the initial state

2017

We explore in a rigorous manner the intuitive connection between the non-Markovianity of the evolution of an open quantum system and the performance of the system as a quantum memory. Using the paradigmatic case of a two-level open quantum system coupled to a bosonic bath, we compute the recovery fidelity, which measures the best possible performance of the system to store a qubit of information. We deduce that this quantity is connected, but not uniquely determined, by the non-Markovianity, for which we adopt the BLP measure proposed in \cite{breuer2009}. We illustrate our findings with explicit calculations for the case of a structured environment.

Statistics and ProbabilityQuantum PhysicsComputer sciencemedia_common.quotation_subjectMeasure (physics)General Physics and AstronomyFidelityFOS: Physical sciencesStatistical and Nonlinear PhysicsState (functional analysis)01 natural sciencesQuantum memory010305 fluids & plasmasConnection (mathematics)Open quantum systemModeling and SimulationQubit0103 physical sciencesStatistical physics010306 general physicsQuantum Physics (quant-ph)Mathematical Physicsmedia_common
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kmcEx: memory-frugal and retrieval-efficient encoding of counted k-mers.

2018

Abstract Motivation K-mers along with their frequency have served as an elementary building block for error correction, repeat detection, multiple sequence alignment, genome assembly, etc., attracting intensive studies in k-mer counting. However, the output of k-mer counters itself is large; very often, it is too large to fit into main memory, leading to highly narrowed usability. Results We introduce a novel idea of encoding k-mers as well as their frequency, achieving good memory saving and retrieval efficiency. Specifically, we propose a Bloom filter-like data structure to encode counted k-mers by coupled-bit arrays—one for k-mer representation and the other for frequency encoding. Exper…

Statistics and ProbabilitySource codeComputer sciencemedia_common.quotation_subject0206 medical engineeringHash function02 engineering and technologyBiochemistry03 medical and health sciencesEncoding (memory)Molecular BiologyTime complexity030304 developmental biologyBlock (data storage)media_common0303 health sciencesSequence Analysis DNAData structureComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsError detection and correctionAlgorithmSequence Alignment020602 bioinformaticsAlgorithmsSoftwareBioinformatics (Oxford, England)
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Juggler's exclusion process

2012

Juggler's exclusion process describes a system of particles on the positive integers where particles drift down to zero at unit speed. After a particle hits zero, it jumps into a randomly chosen unoccupied site. We model the system as a set-valued Markov process and show that the process is ergodic if the family of jump height distributions is uniformly integrable. In a special case where the particles jump according to a set-avoiding memoryless distribution, the process reaches its equilibrium in finite nonrandom time, and the equilibrium distribution can be represented as a Gibbs measure conforming to a linear gravitational potential.

Statistics and Probabilityset-valued Markov processmaximum entropy60K35 82C41General Mathematics82C41FOS: Physical sciencesMarkov process01 natural sciencespositive recurrencesymbols.namesakeGravitational potentialMarkov renewal process0103 physical sciencesjuggling patternFOS: MathematicsErgodic theory0101 mathematicsGibbs measureMathematical PhysicsMathematicsDiscrete mathematicsnoncolliding random walkProbability (math.PR)ta111010102 general mathematicsErgodicityMathematical analysisExclusion processMathematical Physics (math-ph)Gibbs measureDistribution (mathematics)set-avoiding memoryless distribution60K35Jumpsymbolsergodicity010307 mathematical physicsStatistics Probability and UncertaintyMathematics - Probability
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Anomalous diffusion and nonlinear relaxation phenomena in stochastic models of interdisciplinary physics

2020

The study of nonlinear dynamical systems in the presence of both Gaussian and non-Gaussian noise sources is the topic of this research work. In particular, after shortly present new theoretical results for statistical characteristics in the framework of Markovian theory, we analyse four different physical systems in the presence of Levy noise source. (a) The residence time problem of a particle subject to a non-Gaussian noise source in arbitrary potential profile was analyzed and the exact analytical results for the statistical characteristics of the residence time for anomalous diffusion in the form of Levy flights in fully unstable potential profile was obtained. Noise enhanced stability …

Steady-state probability density function (PDF)Settore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciIdeal Chua memristorMemory devicesAnomalous diffusionLevy flightsBarrier crossing eventCorrelation time
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Stereotype Threat Effect on a Simple Motor Task: An Investigation of the Visuo-Spatial Working Memory

2020

Purpose: Based on the Chalabaev et al. (2013) study showing that in a Stereotype Threat (ST) situation the velocity of force production in a simple motor task can be affected, this study aimed to r...

StereotypingMovement030209 endocrinology & metabolismPhysical Therapy Sports Therapy and Rehabilitation030229 sport sciencesGeneral MedicineSpatial memoryStereotype threat03 medical and health sciencesMotor taskCognitionMemory Short-Term0302 clinical medicineNephrologySimple (abstract algebra)HumansFemaleKneeOrthopedics and Sports MedicinePsychologyCognitive psychologyMental imageResearch Quarterly for Exercise and Sport
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Strain-Controlled Giant Magnetoresistance in Spin Valves Grown on Shape Memory Alloys

2019

We report a strain-mediated giant magnetoresistance (GMR) in spin valves (SPVs) grown on shape memory alloys (SMAs). The SPVs with a stacking structure of Al2O3/Co90Fe10/Cu/Co90Fe10/IrMn/Pt were de...

Strain engineeringMaterials scienceCondensed matter physicsStrain (chemistry)Materials ChemistryElectrochemistryStackingSpin valveGiant magnetoresistanceShape-memory alloyElectronic Optical and Magnetic MaterialsSpin-½ACS Applied Electronic Materials
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Are Neural Networks Imitations of Mind?

2015

Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.

Structure (mathematical logic)Artificial neural networkQuantitative Biology::Neurons and CognitionArtificial neural networkComputer sciencebusiness.industryComputationComputer Science::Neural and Evolutionary ComputationAcknowledgementShort-term memoryRecurrent networkBrainFeed-forward networkSettore M-FIL/02 - Logica E Filosofia Della ScienzaPerceptroncomputer.software_genreMindSimilitudeHopfield networkArtificial intelligenceData miningbusinesscomputer
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Firefly algorithm based upon slicing structure encoding for unequal facility layout problem

2019

Finding the locations of departments or machines in a workspace is classified as a Facility Layout Problem. Good placement of departments has a relevant influence on manufacturing costs, work in process, lead times and production efficiency. This paper analyses the problem of allocating departments with restrictions in terms of unequal area and rectangular shape within a facility, in order to minimize the sum of material handling costs taking into account the satisfaction of the aspect ratio requested. In particular, we propose for the first time a Firefly Algorithm based on the slicing structure encoding. The proposed method was tested comparing the results obtained from other authors on t…

Structure (mathematical logic)Firefly protocollcsh:T55.4-60.8Computer scienceSlicingFacility layout problemFirefly algorithm Problem; Slicing structure; Unequal area-facility layoutIndustrial and Manufacturing EngineeringEncoding (memory)Settore ING-IND/17 - Impianti Industriali MeccaniciFirefly algorithm Problem Slicing structure Unequal area-facility layoutFirefly Algorithmlcsh:Industrial engineering. Management engineeringFirefly algorithmUnequal Area-Facility Layout ProblemSlicing Structurelcsh:Production management. Operations managementlcsh:TS155-194AlgorithmInternational Journal of Industrial Engineering Computations
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A multi objective genetic algorithm for the facility layout problem based upon slicing structure encoding

2012

This paper proposes a new multi objective genetic algorithm (MOGA) for solving unequal area facility layout problems (UA-FLPs). The genetic algorithm suggested is based upon the slicing structure where the relative locations of the facilities on the floor are represented by a location matrix encoded in two chromosomes. A block layout is constructed by partitioning the floor into a set of rectangular blocks using guillotine cuts satisfying the areas requirements of the departments. The procedure takes into account four objective functions (material handling costs, aspect ratio, closeness and distance requests) by means of a Pareto based evolutionary approach. The main advantage of the propos…

Structure (mathematical logic)Mathematical optimizationClosenessGeneral EngineeringPareto principleSlicingComputer Science ApplicationsSet (abstract data type)Artificial IntelligenceEncoding (memory)Genetic algorithmMulti Objective Genetic Algorithm Facility Layout ProblemSlicing StructureMathematicsBlock (data storage)Expert Systems with Applications
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