Least Squares Moving-Window Spectral Analysis
نویسندگان
چکیده
منابع مشابه
Multiple Window Least Squares Evolutionary Spectral Analysis
We present a multi–window method for obtaining the time-frequency spectrum of a non–stationary signal. This method is based on optimal combination of evolutionary spectra that are calculated by using multi– window Gabor expansion. The optimal weights are obtained by using a least square estimation method. An error criterion that is the difference between a reference time–frequency distribution ...
متن کاملLeast Squares Multi-Window Evolutionary Spectral Estimation
We present a multi–window method for obtaining the time-frequency spectrum of of nonstationary signals such as speech and music. This method is based on optimal combination of evolutionary spectra that are calculated by using multi–window Gabor expansion. The optimal weights are obtained by using a least square estimation method. An error criterion that is the squared distance between a referen...
متن کاملStable Moving Least-Squares
It is a common procedure for scattered data approximation to use local polynomial fitting in the least-squares sense. An important instance is the Moving Least-Squares where the corresponding weights of the data site vary smoothly, resulting in a smooth approximation. In this paper we build upon the techniques presented by Wendland and present a somewhat simpler error analysis of the MLS approx...
متن کاملMoving Least Squares Coordinates
We propose a new family of barycentric coordinates that have closed-forms for arbitrary 2D polygons. These coordinates are easy to compute and have linear precision even for open polygons. Not only do these coordinates have linear precision, but we can create coordinates that reproduce polynomials of a set degree m as long as degree m polynomials are specified along the boundary of the polygon....
متن کاملMoving Least Squares Approximation
An alternative to radial basis function interpolation and approximation is the so-called moving least squares method. As we will see below, in this method the approximation Pf to f is obtained by solving many (small) linear systems, instead of via solution of a single – but large – linear system as we did in the previous chapters. To make a connection with the previous chapters we start with th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Spectroscopy
سال: 2017
ISSN: 0003-7028,1943-3530
DOI: 10.1177/0003702816685336