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FIR Filter Design via Spectral Factorization and Convex Optimization
FIR Filter Design Spectral Factorization Convex Optimization
2015/7/13
We consider the design of finite impulse response (FIR) filters subject to upper and lower bounds on the frequency response magnitude. The associated optimization problems, with the filter coefficient...
ON THE STABILITY OF CHOLESKY FACTORIZATION FOR SYMMETRIC QUASIDEFINITE SYSTEMS*
indefinite systems symmetric quasidefinite (sqd) systems
2015/7/3
Sparse linear equations Kd r are considered, where K is a specially structured
symmetric indefinite matrix that arises in numerical optimization and elsewhere. Under certain
conditions, K is quaside...
Structural and Functional Discovery in Dynamic Networks with Non-negative Matrix Factorization
Structural Functional Discovery Dynamic Networks Non-negative Matrix Factorization
2013/6/17
Time series of graphs are increasingly prevalent in modern data and pose unique challenges to visual exploration and pattern extraction. This paper describes the development and application of matrix ...
Adaptive Graph via Multiple Kernel Learning for Nonnegative Matrix Factorization
Data Representation Nonnegtive Matrix Factorization Graph Regularization Multiple Kernel Learning.
2012/9/18
Nonnegative Matrix Factorization (NMF) has been contin-uously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank ...
Fast and Robust Recursive Algorithms for Separable Nonnegative Matrix Factorization
nonnegative matrix factorization algorithms separability robustness hyperspectral unmixing linear mixing model pure-pixel assumption
2012/9/17
In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subsetof the columns of the input nonnegative da...
MahNMF: Manhattan Non-negative Matrix Factorization
Non-negative Matrix Factorization (NMF) Nesterov’s Smoothing Method Sparse and Low-rank Matrix Decomposition
2012/9/19
Non-negative matrix factorization (NMF) approximates a non-negative matrix Xby a product of two non-negative low-rank factor matricesWandH. NMF and its extensions minimize either the Kullback-Leibler ...
This work introduces SubMF, a parallel divide-and-conquer framework for noisy matrix factorization.
Online algorithms for Nonnegative Matrix Factorization with the Itakura-Saito divergence
Online algorithms Nonnegative Matrix Factorization Itakura-Saito divergence
2011/7/6
Nonnegative matrix factorization (NMF) is now a common tool for audio source separation.
A convex model for non-negative matrix factorization and dimensionality reduction on physical space
Non-negative matrix factorization dictionary learning subset selection dimensionality reduction hyperspec-tral endmember detection blind source separation
2011/3/18
A collaborative convex framework for factoring a data matrix $X$ into a non-negative product $AS$, with a sparse coefficient matrix $S$, is proposed. We restrict the columns of the dictionary matrix $...
Note on the factorization of the Haar measures on finite Coexter groups
Finite Coxcter groups factorization Haar measure Fourier transform
2009/9/21
In this note we &ow that for the finite Coxeter groups
of types A,, B,, D,, F,, G, and 12(m) it i s possible to choose w appropriate
set S of generators of order not greater than 2 and a finite set
...