Search results for "Kernel"
showing 7 items of 357 documents
Aliasing-Free and Additive Error in Mixed Spectra for Stable Processes. Application: Sound of a Bird just captivated in stress
2022
Consider a symmetric continuous time α stableprocess observed with an additive constant error. Theobjective of this paper is to give a non-parametric estimatorof this error by using discrete observations. As the time ofprocess is continuous and the observations are discrete, weencountered the aliasing phenomenon. Our process sampleis taken in a way to circumvent the difficulty related toaliasing and we smoothed the periodogram by using JacksonKernel. The rate of convergence of this estimator is studiedwhen the spectral density is zero at origin. Few long memoryprocesses are taken here as examples. We have applied ourestimator to the concrete case of modeling noise of a birdcaptured under st…
Broglie and Young, visionaries who shed light in the polar topology that grounds our reality: a hypothesis
2020
Una observación matemática que relaciona los patrones fractales y la operación de convolución en el contexto del procesamiento de imágenes digitales interrumpió una investigación que nos lleva a plantear la hipótesis de que el concepto de onda de materia (o dualidad onda-partícula) se encuentra en la dicotomía entre el par débil y un topología fuerte en el ámbito del marco de atractores singulares continuos en ninguna parte diferenciables y el concepto de fotón-solitón de Vigier. Tal inferencia parece ser más evidente en la interpretación de Broglie-Bohm de la mecánica cuántica en el cruce de características locales x globales. De esto se deduce también que la relación de los fenómenos natu…
Sensitivity analysis of Gaussian processes for oceanic chlorophyll prediction
2015
Gaussian Process Regression (GPR) for machine learning has lately been successfully introduced for chlorophyll content mapping from remotely sensed data. The method provides a fast, stable and accurate prediction of biophysical parameters. However, since GPR is a non-linear kernel regression method, the relevance of the features are not accessible. In this paper, we introduce a probabilistic approach for feature sensitivity analysis (SA) of the GPR in order to reveal the relative importance of the features (bands) being used in the regression process. We evaluated the SA on GPR ocean chlorophyll content prediction. The method revealed the importance of the spectral bands, thus allowing the …
An Improved Method for Estimating the Time ACF of a Sum of Complex Plane Waves
2010
Time averaging is a well-known technique for evaluating the temporal autocorrelation function (ACF) from a sample function of a stochastic process. For stochastic processes that can be modelled as a sum of plane waves, it is shown that the ACF obtained by time averaging can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs result from the autocorrelation of the individual plane waves, while the CTs are due to the cross-correlation between different plane wave components. The CTs cause an estimation error of the ACF. This estimation error increases as the observation time decreases. For the practically important case that the observation time interval is limited, we pr…
COMPLEX CONVEXITY AND VECTOR-VALUED LITTLEWOOD–PALEY INEQUALITIES
2003
Let 2 p 0s uch thatfHp(X) (� f(0)� p + λ (1 −| z| 2 ) p−1 � f � (z)� p dA(z)) 1/p ,f or all f ∈ H p (X). Applications to embeddings between vector-valued BMOA spaces defined via Poisson integral or Carleson measures are provided.
Biased graph walks for RDF graph embeddings
2017
Knowledge Graphs have been recognized as a valuable source for background information in many data mining, information retrieval, natural language processing, and knowledge extraction tasks. However, obtaining a suitable feature vector representation from RDF graphs is a challenging task. In this paper, we extend the RDF2Vec approach, which leverages language modeling techniques for unsupervised feature extraction from sequences of entities. We generate sequences by exploiting local information from graph substructures, harvested by graph walks, and learn latent numerical representations of entities in RDF graphs. We extend the way we compute feature vector representations by comparing twel…
Essence : Reference Architecture for Software Engineering - Representing Essence in Archimate Notation
2018
Essence is a standard for working with methods in software engineering. As such, it can be seen as the reference architecture for software engineering. The Essence consists of the Kernel, and a notation called the Language. This representation is not widely known and likely hinders the adoption of the Essence. This paper represents the work-in-progress of representing the Essence using ArchiMate, the de facto notation for enterprise architecture. Our purpose is to help organisations to adopt Essence by representing it in the language already understood by different stakeholders. peerReviewed