Using a well-known form for the inverse of a symmetric Toeplitz matrix, some results in linear interpolation theory are derived. For an autoregressive process it is shown that interpolation at the midpoint of a data record yields the minimum interpolation error. Also, some results for infinite length interpolators are simply derived. © 1983 IEE
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
The Well-Known Analysis and Synthesis Filters of Linear Prediction Theory Are Extended Here to Inclu...
Using a well-known form for the inverse of a symmetric Toeplitz matrix, some results in linear inter...
Linear interpolation is the computationally simplest of all possible interpolation techniques. Inter...
An upper bound is obtained for the restoration error variance of a sample restoration method for aut...
A novel method for computing the minimal eigenvalue of a symmetric positive definite Toeplitz matrix...
The autoregressive and window estimators of the inverse variance, Ri (0), say, are adopted for estim...
A lecture note introducing the sampling theorem as an interpolation method is presented. The relatio...
We propose a minimum mean absolute error linear interpolator (MMAELI), based on the L1 approach. A l...
Understanding when and why interpolating methods generalize well has recently been a topic of intere...
A lecture note introducing the sampling theorem as an interpolation method is presented. The relatio...
The polynomial interpolation in one dimensional space R is an important method to approximate the fu...
Uma aula sobre o teorema da amostragem como um método de interpolação e ́ apresentada neste traba...
The Well-Known Analysis and Synthesis Filters of Linear Prediction Theory Are Extended Here to Inclu...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
The Well-Known Analysis and Synthesis Filters of Linear Prediction Theory Are Extended Here to Inclu...
Using a well-known form for the inverse of a symmetric Toeplitz matrix, some results in linear inter...
Linear interpolation is the computationally simplest of all possible interpolation techniques. Inter...
An upper bound is obtained for the restoration error variance of a sample restoration method for aut...
A novel method for computing the minimal eigenvalue of a symmetric positive definite Toeplitz matrix...
The autoregressive and window estimators of the inverse variance, Ri (0), say, are adopted for estim...
A lecture note introducing the sampling theorem as an interpolation method is presented. The relatio...
We propose a minimum mean absolute error linear interpolator (MMAELI), based on the L1 approach. A l...
Understanding when and why interpolating methods generalize well has recently been a topic of intere...
A lecture note introducing the sampling theorem as an interpolation method is presented. The relatio...
The polynomial interpolation in one dimensional space R is an important method to approximate the fu...
Uma aula sobre o teorema da amostragem como um método de interpolação e ́ apresentada neste traba...
The Well-Known Analysis and Synthesis Filters of Linear Prediction Theory Are Extended Here to Inclu...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
Algorithms for the restoration of unknown samples at known positions embedded in a neighborhood of k...
The Well-Known Analysis and Synthesis Filters of Linear Prediction Theory Are Extended Here to Inclu...
DOI
Add to ORKG