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Redundancy relations for fault diagnosis in nonlinear uncertain systems

Alexey Shumsky (2007)

International Journal of Applied Mathematics and Computer Science

The problem of fault detection and isolation in nonlinear uncertain systems is studied within the scope of the analytical redundancy concept. The problem solution involves checking the redundancy relations existing among measured system inputs and outputs. A novel method is proposed for constructing redundancy relations based on system models described by differential equations whose right-hand sides are polynomials. The method involves a nonlinear transformation of the initial system model into...

Reference points based recursive approximation

Martina Révayová, Csaba Török (2013)

Kybernetika

The paper studies polynomial approximation models with a new type of constraints that enable to get estimates with significant properties. Recently we enhanced a representation of polynomials based on three reference points. Here we propose a two-part cubic smoothing scheme that leverages this representation. The presence of these points in the model has several consequences. The most important one is the fact that by appropriate location of the reference points the resulting approximant of two...

Reference points based transformation and approximation

Csaba Török (2013)

Kybernetika

Interpolating and approximating polynomials have been living separately more than two centuries. Our aim is to propose a general parametric regression model that incorporates both interpolation and approximation. The paper introduces first a new r -point transformation that yields a function with a simpler geometrical structure than the original function. It uses r ≥ 2 reference points and decreases the polynomial degree by r - 1 . Then a general representation of polynomials is proposed based on r ≥ 1 reference...

Refined rates of bias convergence for generalized L-Statistics in the i.i.d. case

George Anastassiou, Tomasz Rychlik (1999)

Applicationes Mathematicae

Using tools of approximation theory, we evaluate rates of bias convergence for sequences of generalized L-statistics based on i.i.d. samples under mild smoothness conditions on the weight function and simple moment conditions on the score function. Apart from standard methods of weighting, we introduce and analyze L-statistics with possibly random coefficients defined by means of positive linear functionals acting on the weight function.

Reflexiones sobre la estrategia de medida de los cambios en probabilidad en modelos de elección binarios.

M.ª Teresa Aparicio Aspas, Inmaculada Villanúa Martín (1998)

Qüestiió

Este trabajo se centra en la evaluación de la medida que, en el marco de los modelos de elección binarios o dicotómicos, se utiliza para reflejar el cambio en la probabilidad ante la variación de una de las variables explicativas. La opción de cuantificación más común ha consistido en utilizar el vector de valores medios de las variables explicativas, lo que podemos entender como poner el énfasis en el comportamiento de un "individuo medio". Frente a esta práctica habitual, efectuamos una propuesta...

Regime-switching models of time series with cubic spline transition function in geodetic application

Tomáš Bognár, Jozef Komorník, Magda Komorníková (2004)

Kybernetika

A new class of Smooth Transition Autoregressive models, based on cubic spline type transition functions, has been introduced and subjected to comparison with models based on the traditional logistic transition functions. A very high degree of similarity between the two model classes has been demonstrated. The new class of models can be slightly preferable because of its more simple formal and geometrical structure that may enable users more convenient manipulation in statistical inference procedures....

Regresión espectral sesgada.

Fernando Tusell Palmer (1988)

Trabajos de Estadística

Se propone un método de regresión espectral adecuado cuando los regresores tienen potencia espectral despreciable sobre bandas de frecuencia estrechas. Se investiga la relación entre el método propuesto y los procedimientos de regresión sesgada habituales en el dominio del tiempo.

Regresión ortogonal y componentes principales.

J. Alberto Martínez Arnáiz (1994)

Qüestiió

In this work the Principal Components Analysis is presented, starting from the orthogonal regression plane. On this basis, the data reduction technique is exposed in the three-dimensional case. Finally, the correlation matrix analysis is considered, as well as its extension to p dimensions.

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