نتایج جستجو برای: incoherent signal subspace

تعداد نتایج: 440299  

Journal: :journal of electrical and computer engineering innovations 0
somaye jalaei digital communications signal processing (dcsp) research lab., faculty of electrical engineering, shahid rajaee teacher training university (srttu), lavizan, 16788-15811, tehran, iran shahriar shirvani moghaddam digital communications signal processing (dcsp) research lab., faculty of electrical engineering, shahid rajaee teacher training university (srttu), lavizan, 16788-15811, tehran, iran

in this paper, a new approach for estimating the number of wideband sources is proposed which is based on rss or ism algorithms. numerical results show that the mdl-based and eit-based proposed algorithm havea much better detection performance than that in egm and aic cases for small differences between the incident angles of sources. in addition, for similar conditions, rss algorithm offers hi...

2009
SANDEEP SANTOSH MONIKA AGGARWAL Sandeep Santosh O. P. Sahu Monika Aggarwal

The Direction of Arrival (DOA) estimation methods are useful in Sonar, Radar and Advanced Satellite and Cellular Communication systems. In this paper different Direction of Arrival(DOA) methods such as Coherent Signal Subspace Processing (CSSM), the Weighted Average of Signal Subspaces (WAVES) and Test of Orthogonality of Projected Subspaces (TOPS) and Incoherent MUSIC(IMUSIC) is presented and ...

In this paper, a new method is proposed for DOA estimation of correlated acoustic signals, in the presence of unknown spatial correlation noise. By generating a matrix from the signal subspace with the Hankel-SVD method, the correlated resource information is extracted from each eigen-vector. Then a joint-diagonalization  structure is constructed of the signal subspace and basis it, independent...

This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

Journal: :the modares journal of electrical engineering 2006
mostafa yargholi mojtaba lotfizad

different methods exists for jamming mitigation and we should choose a method based an the jammer type and other parameters. one of the jammers is narrow band fm jammer and we use subspace projection techniques for the suppression of this type of jammer. in subspace projection technique, we estimate the if of signals and construct the subspace vector that is orthogonal to jammer vector by incre...

Journal: :journal of advances in computer research 2010
amin zehtabian behzad zehtabian

this article presents a new subspace-based technique for reducing the noise ofsignals in time-series. in the proposed approach, the signal is initially representedas a data matrix. then using singular value decomposition (svd), noisy datamatrix is divided into signal subspace and noise subspace. in this subspace division,each derivative of the singular values with respect to rank order is used ...

In this paper, a new approach for estimating the number of wideband sources is proposed which is based on RSS or ISM algorithms. Numerical results show that the MDL-based and EIT-based proposed algorithm havea much better detection performance than that in EGM and AIC cases for small differences between the incident angles of sources. In addition, for similar conditions, RSS algorithm offers hi...

Journal: :Machine Learning 2021

This paper establishes the algorithmic principle of alternating projections onto incoherent low-rank subspaces (APIS) as a unifying for designing robust regression algorithms that offer consistent model recovery even when significant fraction training points are corrupted by an adaptive adversary. APIS offers first algorithm non-parametric (kernel) with explicit breakdown point works general PS...

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