Search results for "parametric"
showing 10 items of 980 documents
The impact of sample reduction on PCA-based feature extraction for supervised learning
2006
"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimensions. In this paper, different feature extraction (FE) techniques are analyzed as means of dimensionality reduction, and constructive induction with respect to the performance of Naive Bayes classifier. When a data set contains a large number of instances, some sampling approach is applied to address the computational complexity of FE and classification processes. The main goal of this paper is to show the impact of sample reduction on the process of FE for supervised learning. In our study we analyzed the conventional PC…
Response Determination Criteria for ELISPOT: Toward a Standard that Can Be Applied Across Laboratories
2011
ELISPOT assay readout is often dichomized as positive or negative responses according to prespecified criteria. However, these criteria can vary widely across institutions. The adoption of a common response criterion is a key step toward cross-laboratory comparability. This chapter describes the two main approaches to response determination, identifying the strengths and limitations of each. Nonparametric statistical tests and consideration of data quality are recommended and instructions provided for their ready implementation by nonstatisticians and statisticians alike.
Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue
2008
In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.
Imbalance Effects in the Lucas Model: An Analytical Exploration
2004
In this note, we use a technique analogous to Xie's method (1994) to solve analytically the Lucas model with externality in a specific parametric case. In particular, we characterize the shape of imbalance effects in this model. Our results are entirely consistent with the findings of the related computational literature. Moreover, our analytical investigation tends to show that these findings are robust to the presence of the Lucas externality as long as a unique equilibrium path exist.
An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains
2021
Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…
Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection
2012
Early detection of ventricular fibrillation (VF) is crucial for the success of the defibrillation therapy in automatic devices. A high number of detectors have been proposed based on temporal, spectral, and time-frequency parameters extracted from the surface electrocardiogram (ECG), showing always a limited performance. The combination ECG parameters on different domain (time, frequency, and time-frequency) using machine learning algorithms has been used to improve detection efficiency. However, the potential utilization of a wide number of parameters benefiting machine learning schemes has raised the need of efficient feature selection (FS) procedures. In this study, we propose a novel FS…
Maximizing reading: pattern analysis to describe points of gaze
2006
As people read texts, their points of gaze can be described either as a sequence or as a pattern of dots. If reading fixations are visualized as a pattern and their duration is graphically attributed to the 3 rd dimension, image processing techniques can be employed to describe individual reading styles. Two reader groups of text editors and of University students were matching according to parametric tests. Yet they appeared to have marked inter-subject variability of fixation distribution when individual cases were considered. To illustrate this, we applied a simple "Coulomb law" - like model that takes both fixation duration and spacing into account. Further the image entropy filter was …
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model
2017
[EN] Spatial audio-rendering techniques using head-related transfer functions (HRTFs) are currently used in many different contexts such as immersive teleconferencing systems, gaming, or 3-D audio reproduction. Since all these applications usually involve real-time constraints, efficient processing structures for HRTF modeling and interpolation are necessary for providing real-time binaural audio solutions. This letter presents a parametric parallel model that allows us to perform HRTF filtering and interpolation efficiently from an input HRTF dataset. The resulting model, which is an adaptation from a recently proposed modeling technique, not only reduces the size of HRTF datasets signific…
Mixed-aspect fractal surfaces
2013
In order to provide accurate tools to model original surfaces in a Computer Aided Geometric Design context, we develop a formalism based on iterated function systems. This model enables us to represent both smooth and fractal free-form curves and surfaces. But, because of the self-similarity property underlying the iterated function systems, curves and surfaces can only have homogeneous roughness. The aim of our work was to elaborate a method to build parametric shapes (curves, surfaces, ...) with a non-uniform local aspect: every point is assigned a ''geometric texture'' that evolves continuously from a smooth to a rough aspect. The principle is to blend shapes with uniform aspects to defi…
Optical Fibers Enter a New Space-Time Era
2016
We show experimentally a new type of parametric instability associated with the original phenomenon of beam self-cleaning in multimode fibers. Our experimental results are in good agreement with numerical solutions of the Gross-Pitaevskii equation.