Search results for "learning theory"

showing 10 items of 216 documents

A Novel Approach to Introducing Adaptive Filters Based on the LMS Algorithm and Its Variants

2004

This paper presents a new approach to introducing adaptive filters based on the least-mean-square (LMS) algorithm and its variants in an undergraduate course on digital signal processing. Unlike other filters currently taught to undergraduate students, these filters are nonlinear and time variant. This proposal introduces adaptive filtering in the context of a linear time-invariant system using a real problem. In this way, introducing adaptive filters using concepts already familiar to the students motivates their interest through practical application. The key point for this simplification is that the input to the filter is constant so that the adaptive filter becomes linear. Therefore, a …

Signal processingTheoretical computer sciencebusiness.industryComputer scienceStability (learning theory)Physics::Physics EducationContext (language use)Filter (signal processing)EducationAdaptive filterLeast mean squares filterComputer engineeringConvergence (routing)ComputingMilieux_COMPUTERSANDEDUCATIONElectrical and Electronic EngineeringbusinessDigital signal processingIEEE Transactions on Education
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Generalized singly-implicit Runge-Kutta methods with arbitrary knots

1985

The aim of this paper is to derive Butcher's generalization of singly-implicit methods without restrictions on the knots. Our analysis yields explicit computable expressions for the similarity transformations involved which allow the efficient implementation of the first phase of the method, i.e. the solution of the nonlinear equations. Furthermore, simple formulas for the second phase of the method, i.e. computation of the approximations at the next nodal point, are established. Finally, the matrix which governs the stability of the method is studied.

Similarity (geometry)Computer Networks and CommunicationsGeneralizationApplied MathematicsComputationMathematical analysisStability (learning theory)Computational MathematicsMatrix (mathematics)Runge–Kutta methodsNonlinear systemSimple (abstract algebra)SoftwareMathematicsBIT
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Change, Reliability, and Stability in Self-perceptions in Early Adolescence: A Four-year Follow-up Study

1995

Changes in self-perceptions of fitness, appearance, and self-esteem among adolescents were assessed in a 4-year follow-up study. Both the changes in the mean levels across time (profile analysis), and the changes in the reliability and stability of individual differences (i.e. covariance stability as test-retest correlations) were examined. The subjects (64 boys, 49 girls) were 11 years old at the first annual measurement. Self-esteem was assessed using the Rosenberg Self-Esteem Scale, as well as self-assessment questionnaires specifically designed for this study to assess Perceived Fitness and Perceived Appearance. MANOVA-and Simplex-models were used in the analysis. Our results among the…

Social PsychologyEarly adolescencemedia_common.quotation_subject05 social sciencesStability (learning theory)Follow up studies030229 sport sciences050105 experimental psychologyEducationDevelopmental psychology03 medical and health sciences0302 clinical medicineDevelopmental NeurosciencePerceptionDevelopmental and Educational Psychology0501 psychology and cognitive sciencesProfile analysissense organsLife-span and Life-course StudiesPsychologySocial Sciences (miscellaneous)Reliability (statistics)media_commonInternational Journal of Behavioral Development
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I-states-as-objects-analysis (ISOA): Extensions of an approach to studying short-term developmental processes by analyzing typical patterns

2012

I-states-as-objects-analysis (ISOA) is a person-oriented methodology for studying short-term developmental stability and change in patterns of variable values. ISOA is based on longitudinal data with the same set of variables measured at all measurement occasions. A key concept is the i-state, defined as a person’s pattern of variable values at a specific time point. All i-states are first subjected to a classification analysis that results in a time-invariant classification characterized by a number of typical i-states. Each person is then characterized at each time point by the typical i-state he/she belongs to. Then the person’s sequences of typical i-states are analyzed with regard to …

Social Psychologybusiness.industryStability (learning theory)Pattern recognitionDegree (music)Structural equation modelingEducationTerm (time)Developmental NeuroscienceSample size determinationStatisticsDevelopmental and Educational PsychologyArtificial intelligenceTime pointLife-span and Life-course StudiesbusinessSet (psychology)Social Sciences (miscellaneous)ta515Variable (mathematics)MathematicsInternational Journal of Behavioral Development
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The Stability Theory of Knowledge and Belief Revision: Comments on Rott

2005

In this commentary on Rott’s paper “Stability, Strength and Sensitivity: Converting Belief into Knowledge”, I discuss two problems of the stability theory of knowledge which are pointed out by Rott. I conclude that these problems offer no reason for rejecting the stability theory, but might be grounds for deviating from the standard AGM account of belief revision which Rott presupposes.

Stability theoryOntologyStability (learning theory)Sensitivity (control systems)Belief revisionEpistemologyMathematics
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On stability issues in deriving multivariable regression models

2014

In many areas of science where empirical data are analyzed, a task is often to identify important variables with influence on an outcome. Most often this is done by using a variable selection strategy in the context of a multivariable regression model. Using a study on ozone effects in children (n = 496, 24 covariates), we will discuss aspects relevant for deriving a suitable model. With an emphasis on model stability, we will explore and illustrate differences between predictive models and explanatory models, the key role of stopping criteria, and the value of bootstrap resampling (with and without replacement). Bootstrap resampling will be used to assess variable selection stability, to d…

Statistics and ProbabilityMultivariable calculusStability (learning theory)Context (language use)Regression analysisFeature selectionGeneral MedicineVariance (accounting)StatisticsCovariateEconometricsStatistics Probability and UncertaintySelection (genetic algorithm)MathematicsBiometrical Journal
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New adaptive synchronization algorithm for a general class of complex hyperchaotic systems with unknown parameters and its application to secure comm…

2022

Abstract The aim of this report is to investigate an adaptive synchronization (AS) for the general class of complex hyperchaotic models with unknown parameters and a new algorithm to achieve this type of synchronization is proposed. Owing to the intricacy behavior of hyperchaotic models that could be effective in secure communications, the special control based on adaptive laws of parameters is constructed analytically, and the corresponding simulated results are performed to validate the algorithm’s accuracy. The complex Rabinovich model is utilized as an enticing example to examine the proposed synchronization technique. A strategy for secure communication improving the overall cryptosyst…

Statistics and Probabilitybusiness.industryComputer scienceTransmitterStability (learning theory)Statistical and Nonlinear Physicssymbols.namesakeAdditive white Gaussian noiseSecure communicationRobustness (computer science)Gaussian noiseSynchronization (computer science)symbolsCryptosystembusinessAlgorithmPhysica A: Statistical Mechanics and its Applications
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On stability and dissipativity of stochastic nonlinear systems

2012

Input-to-state stability of nonlinear control system is described in several different manners, and has been a central concept since the equivalences among them were verified. In this paper, a framework of stability and dissipativity for stochastic control systems is constructed on the maximal existence interval of behaviors (states and external inputs), by the aid of stochastic Barbalat lemma and stochastic dissipativity. The main work consists of three aspects. First, input-to-state stability and robust stability are extended to the stochastic case, and several criteria are established. Second, two forms of dissipativity and their criteria are presented. Third, the key relations among the…

Stochastic controlNonlinear systemWork (thermodynamics)Lemma (mathematics)Control theoryStability (learning theory)Interval (mathematics)Nonlinear controlLipschitz continuityMathematics2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
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Set-valued and fuzzy stochastic differential equations driven by semimartingales

2013

Abstract In the paper we present set-valued and fuzzy stochastic integrals with respect to semimartingale integrators as well as their main properties. Then we study the existence of solutions to set-valued and fuzzy-set-valued stochastic differential equations driven by semimartingales. The stability of solutions is also established.

Stratonovich integralApplied MathematicsMathematical analysisStochastic calculusStability (learning theory)Fuzzy logicSet (abstract data type)Stochastic partial differential equationStochastic differential equationSemimartingaleMathematics::ProbabilityApplied mathematicsAnalysisMathematicsNonlinear Analysis-Theory Methods & Applications
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Invited commentary: Differential learning is different from contextual interference learning.

2016

There has been renewed interest in the detailed structure of what is learned and the boundary conditions that foster motor learning. The accompanying article by Hossner et al. (2016), particularly their findings about augmented feedback in the context of different levels of additional noise, is consistent with this focus. Unfortunately, the findings from Hossner and colleagues appear to be based on incorrect interpretations of the differential learning (DL) approach. Essential discrepancies in the experimental conditions suggest the basis for the deviating results obtained in comparison to those of the original DL experiments. In this comment, it is also shown that the author's assumptions …

Structure (mathematical logic)BiophysicsExperimental and Cognitive PsychologyContext (language use)030229 sport sciencesGeneral MedicineFocus (linguistics)Feedback03 medical and health sciences0302 clinical medicineDifferential learningAugmented feedbackLearning theoryHumansLearningOrthopedics and Sports MedicineMotor learningPsychologySocial psychology030217 neurology & neurosurgeryCognitive psychologyHuman movement science
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