Search results for "Parametric"

On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods for Three-Dimensional Environments

2019

We consider the unsolved problem of Distance Estimation (DE) when the inputs are the x and y coordinates (i.e., the latitudinal and longitudinal positions) of the points under consideration, and the elevation/altitudes of the points specified, for example, in terms of their z coordinates (3DDE). The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by all the three coordinates of the cities in question (This is a typical problem encountered in a GISs and GPSs.). In our setting, the distance between any pair of cities is assumed to be computed by merely having access to the coordinates and known inter-city distances of a small subset o…

BICKEL–ROSENBLATT TEST FOR WEAKLY DEPENDENT DATA

2012

The aim of this paper is to analyze the Bickel–Rosenblatt test for simple hypothesis in case of weakly dependent data. Although the test has nice theoretical properties, it is not clear how to implement it in practice. Choosing different band-width sequences first we analyze percentage rejections of the test statistic under H0 by some empirical simulation analysis. This can serve as an approximate rule for choosing the bandwidth in case of simple hypothesis for practical implementation of the test. In the recent paper [12] a version of Neyman goodness-of-fit test was established for weakly dependent data in the case of simple hypotheses. In this paper we also aim to compare and discuss the …

Berry Phase and Parametric Harmonic Oscillator

2001

Our concern in this section is once more with the time-dependent harmonic oscillator with Lagrangian $$\displaystyle{ L = \frac{1} {2}\dot{x}^{2} -\frac{1} {2}\omega ^{2}(t)x^{2}\;. }$$ To present a coherent picture of the whole problem, let us briefly review some of the results of Chap. 21. There we found the propagation function

Semi-parametric estimation of the intensity function in space-time point processes

2009

Exploiting the optical quadratic nonlinearity of zinc-blende semiconductors for guided-wave terahertz generation: A material comparison

2010

We present a detailed analysis and comparison of dielectric waveguides made of CdTe, GaP, GaAs and InP for modal phase matched optical difference frequency generation (DFG) in the terahertz domain. From the form of the DFG equations, we derived the definition of a very general figure of merit (FOM). In turn, this FOM enabled us to compare different configurations, by taking into account linear and nonlinear susceptibility dispersion, terahertz absorption, and a rigorous evaluation of the waveguide modes properties. The most efficient waveguides found with this procedure are predicted to approach the quantum efficiency limit with input optical power in the order of kWs.

Segmentation algorithm for non-stationary compound Poisson processes

2010

We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algori…

Experimental approach for testing the uncoupling between cardiovascular variability series

2002

In cardiovascular variability analysis, the significance of the coupling between two series is commonly assessed by defining a zero level on the magnitude-squared coherence (MSC). Although the use of the conventional value of 0.5 does not consider the dependence of MSC estimates on the analysis parameters, a theoretical threshold Tt is available only for the weighted covariance (WC) estimator. In this study, an experimental threshold for zero coherence Te was derived by a statistical test from the sampling distribution of MSC estimated on completely uncoupled time series. MSC was estimated by the WC method (Parzen window, spectral bandwidth B = 0.015, 0.02, 0.025, 0.03 Hz) and by the parame…

Modeling Ordinal Item Responses via Binary GLMMs and Alternative Link Functions: An Application to Measurement of a Perceived Service Quality

2010

Evaluation of a service on the basis of consumer opinion is a widespread practice in many fields. The assessment of perceived quality [7] of a service is generally carried out through administration of a questionnaire, composed of several items with responses posed on an ordinal scale, whereby each item represents an important feature of the evaluated service [3, 7]. In this context, the aim is to evaluate something similar to the external effectiveness, that is the part of efficacy related to the satisfaction expressed by the service users for the provided service. A particular and important example of service users is represented by students’ responses measuring the perceived quality of s…

On Automaton Recognizability of Abnormal Extremals

2002

For a generic single-input planar control system $\dot x=F(x)+ u G(x),$ $x\in\mathbb{R}^2,$ $u\in [-1,1]$, $F(0)=0$, we analyze the properties of abnormal extremals for the minimum time stabilization to the origin. We prove that abnormal extremals are finite concatenations of bang arcs with switchings occurring on the set in which the vector fields F and G are collinear. Moreover, all the generic singularities of one parametric family of extremal trajectories near to abnormal extremals are studied. In particular, we prove that all possible sequences of these singularities, and hence all generic abnormal extremals, can be classified by a set of words recognizable by an automaton.

On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods

2018

In this paper, we consider the problem of Distance Estimation (DE) when the inputs are the x and y coordinates of the points under consideration. The aim of the problem is to yield an accurate value for the real (road) distance between the points specified by the latter coordinates. This problem has, typically, been tackled by utilizing parametric functions called Distance Estimation Functions (DEFs). The parameters are learned from the training data (i.e., the true road distances) between a subset of the points under consideration. We propose to use Learning Automata (LA)-based strategies to solve the problem. In particular, we resort to the Adaptive Tertiary Search (ATS) strategy, propose…