Non-Negative Matrix Factorization Based UKF Algorithm for Constant Modulus Signals in Adaptive Beamforming

On blind beamforming for multiple non-Gaussian signals and the constant-modulus algorithm

In a recent paper, Sheinvald compared a cumulant matching criterion to three simplified criteria that he claimed to be equivalent. We show that two simplified criteria can be viewed as direct consequences of a result already published and that their equivalence must be revised. We also give additional references of closely related works that have been omitted, some of them presenting Jacobi-lik...

Blind Adaptive Beamforming Based on Constrained Constant Modulus RLS Algorithm for Smart Antennas

In this paper, we study the performance of blind adaptive beamforming algorithms for smart antennas in realistic environments. A constrained constant modulus (CCM) design criterion is described and used for deriving a recursive least squares (RLS) type optimization algorithm. Furthermore, two kinds of scenarios are considered in the paper for analyzing its performance. Simulations are performed...

Adaptive Noise Estimation Based on Non-negative Matrix Factorization

In this paper, an adaptive noise estimation technique is proposed on the basis of non-negative matrix factorization (NMF). As an initial step of the proposed method, the noise basis matrix of NMF is estimated from a collection of noise signals. Then, the proposed method updates the initially estimated noise basis matrix on the fly by using an estimate of the noise spectrum from the noisy signal...

Iterative Weighted Non-smooth Non-negative Matrix Factorization for Face Recognition

Non-negative Matrix Factorization (NMF) is a part-based image representation method. It comes from the intuitive idea that entire face image can be constructed by combining several parts. In this paper, we propose a framework for face recognition by finding localized, part-based representations, denoted “Iterative weighted non-smooth non-negative matrix factorization” (IWNS-NMF). A new cost fun...

Non-negative matrix factorization