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Utilizing the difference in phase and power spectrum between signals and noise, the estimation of direction of arrival (DOA) can be transferred to a spatial sample classification problem. The power ratio, namely signal-to-noise ratio (SNR), is highly required in most high-resolution beamforming methods so that high resolution and robustness are incompatible in a noisy background. Therefore, this paper proposes a Subspaces Deconvolution Vector (SDV) beamforming method to improve the robustness of a high-resolution DOA estimation. In a noisy environment, to handle the difficulty in separating signals from noise, we intend to initial beamforming value presets by incoherent eigenvalue in the frequency domain. The high resolution in the frequency domain guarantees the stability of the beamforming. By combining the robustness of conventional beamforming, the proposed method makes use of the subspace deconvolution vector to build a high-resolution beamforming process. The SDV method is aimed to obtain unitary frequency matrixes more stably and improve the accuracy of signal subspaces. The results of simulations and experiments show that when the input SNR is less than −27 dB, signals of decomposition differ unremarkably in the subspace while the SDV method can still obtain clear angles. In a marine background, this method works well in separating the noise and recruiting the characteristics of the signal into the DOA for subsequent processing.

We distinguish the two extreme aspects of the logic of certainty by identifying their corresponding structures into a linear space. We extend probability laws P formally admissible in terms of coherence to random quantities. We give a geometric representation of these laws P and of a coherent prevision function P which we previously defined in an original way. We are the first in the world to do this kind of work: it is the foundation of our next and extensive study concerning the formulation of a geometric, wellorganized and original theory of random quantities.

In this paper authors for the first time introduce the concept of Neutrosophic Quadruple (NQ) vector spaces and Neutrosophic Quadruple linear algebras and study their properties. Most of the properties of vector spaces are true in case of Neutrosophic Quadruple vector spaces. Two vital observations are, all quadruple vector spaces are of dimension four, be it defined over the field of reals R or the field of complex numbers C or the finite field of characteristic p, Z p ; p a prime. Secondly all of them are distinct and none of them satisfy the classical property of finite dimensional vector spaces. So this problem is proposed as a conjecture in the final section.

Spherical antenna array (SAA) exhibits the ability to receive electromagnetic (EM) waves with the same signal strength, regardless of the direction-of-arrival (DoA), angle-of-arrival, and polarization. Hence, estimating the DoA of EM signals that impinge on SAA in the presence of mutual coupling requires research consideration. In this paper, a subspace pseudointensity vectors technique is proposed for DoA estimation using SAA with unknown mutual coupling. DoA estimation using an intensity vector technique is appealing due to its computational efficiency, particularly for SAAs. Two intensity vector-based techniques that operate with spherical harmonic decomposition (SHD) of an EM wave obtained from SAA are presented. The first technique employed pseudointensity vectors (PV) and operates quite well under EM conditions when one source is in operation each time, while the second technique employed subspace pseudointensity vectors (SPV) and operates under EM conditions when multi-sources and multiple reflection cause more challenging problems. The degree of correctness in the estimation of the DoA via the PVs and SPVs is measured using baseline methods in the literature via simulations, adding noise to stationary, single-source and multi-source methods. In addition, incorporating mutual coupling effects, data from experiments, which are the generally acceptable ground truth when examining any procedure, are further used to illustrate the robustness and efficiency of the proposed techniques. The results are sufficiently inspiring for the practical deployment of the proposed techniques.

The construction of bi-frames is a fundamental problem in frame theory. Due to their wide applications, the study of vector-valued frames and subspace frames has interested many mathematicians in recent years. In this paper, we introduce the weak Gabor bi-frame (WGBF) in vector-valued subspaces, characterize WGBFs on the time domain, and present some examples.

We introduce the notion of an operating function on a subset of a -algebra E . Then we use this notion to generalize results from Huijsmans and de Pagter (Proc. Lond. Math. Soc. 48:161–174, 1984) about the connection between vector subspaces and subalgebras of E . In the second part we investigate the analogous problem for operators.

In this paper, we introduce the notion of normal fuzzy subspace of vector spaces. By using it, we construct new fuzzy subspaces. We also show that, under certain conditions, a fuzzy subspace of a vector space is two-valued and takes 0 and 1.

In this paper we provide an actual bound for the distance between the original and the perturbed right singular vector subspaces of a general matrix with full column rank. We also provide actual relative componentwise bounds for perturbed eigenvectors of a positive definite matrix.

An abstract characterization for those irrational rotation unitary systems with complete wandering subspaces is given. We prove that an irrational rotation unitary system has a complete wandering vector if and only if the von Neumann algebra generated by the unitary system is finite and shares a cyclic vector with its commutant. We solve a factorization problem of Dai and Larson negatively for wandering vector multipliers, and strengthen this by showing that for an irrational rotation unitary system U, every unitary operator in w*(U) is a wandering vector multiplier. Moreover, we show that there is a class of wandering vector multipliers, induced in a natural way by pairs of characters of the integer group Z, which fail to factor even as the product of a unitary in U′and a unitary in w*(U). Incomplete maximal wandering subspaces are also considered, and some questions are raised.

Not only the vectors of a vector space V are interesting, but also those subsets of the vector space that are themselves vector spaces when the opertaions of V are restricted to them. Such subsets are called vector subspaces or linear subspaces.