(1) Our physical forms are inhabited by our subspace forms.

(2) These estimators include the signal subspace methods, ESPRIT and WSF. They possess good statistical performance.

(3) A methodology, called Signal Subspace Correlation ( SSC ), is introduced.

(4) Based on the idea of frequency domain subspace, a multipath delay estimating method for aperiodic spreading system is proposed.

(5) Compared with general statistical feature subspace operation was needed in forming the adaptive feature subspace.

(6) Subspace method is an efficient tool for generalized eigenvalue problem in scientific and engineering computing.

(7) And thirdly with stochastic subspace inversion method it reduces the number of dimensions of inversion.

(8) If we do VQ at the lower dimensional subspace(http:///subspace.html), the computing complexity can be reduced.

(9) They lead students through introductory experiences in telepathy and techniques of subspace communication and energy manipulation.

(10) Computer simulation results show that the algorithm in this paper obtained better performance than the coherent signal subspace algorithm and reduced the computation complexity.

(11) An estimated algorithm of face pose based on the independence subspace analysis ( ISA ) technique is presented.

(12) After the equation is set up, using the standard finite element program and subspace iteration algorithm to solve the generalized eigenvalue problem.

(13) First, we relax the uncertainty set to be intersection of a closed convex cone and the translation of an affine subspace.

(14) By lattice-theoretic methods we give a necessary and sufficient condition for a continuous mapping with the codomain T_3 to be extended continuously from a dense subspace to the whole space.

(15) This paper devises a QSDHMM training algorithm to estimate QSDHMM parameters directly from speech data if having a prior knowledge of the subspace distribution tying structure of the system (SDTS).

(16) It brings up a new DS - CDMA multiuser interference suppression receiver with a subspace tracking adaptive array.

(17) So we study the closed - loop identification problem of subspace.

(18) One is the method based on minimum output energy ( MOE ), the other is the subspace approach.

(19) In this paper , the matrix iteration method and subspace iteration method are improved.

(20) A linear iterative method for projective reconstruction based on 1 D subspace is presented in the paper.

(21) What could possibly exert that kind of influence on a subspace matter stream?

(22) These observations allow one to formalize the definition of reflection: a reflection is an involutive isometry of an Euclidean space whose set of fixed points is an affine subspace of codimension 1.

(23) A modified ULV updating algorithm. is applied to performing noise subspace tracking. The algorithm does not require rank estimation of the correlation matrix, and estimate directly the noise subspace.

(24) Experiments on speaker identification performance analysis demonstrate effectiveness of subspace method, especially for short time test speech with length less than or equal to 3 seconds.

(25) The fundamental circuits relative to a spanning tree is a basis of the circ subspace.

(26) The isomorphic conditions of some lattices generated sets of subspace under finite pseudo - symplectic groups are discussed.

(27) A time optimal control method switched by time is put forward in the paper based on the concept of subspace of the initial state space. It doesn′t need switching curve or switching surface.

(28) It will demagnetize the strips on all your credit cards, reprogram your ATM access code, screw up the tracking on your VCR and use subspace field harmonics to scratch any CDs you try to play.

(29) Basing on the signal space model, the harmonics in power system was detected by combining the subspace rotational invariance and least squares method.

(30) Active Shape Models use the orthogonal projection to the shape subspace, neglecting the information during the search procedure.

(31) Different target classes were modeled as subspace random signals that may belong to different signal subspaces specified by corresponding projection matrices.

(32) At the same time, the approximate expression of the eigen spectrum caused by LSM's rotation and the upper bound disturbed theorem of Learning Subspace are presented.

(33) Two quantitative indexes, projection residual as well as included angle of subspace, are also proposed to measure the difference of two subspaces.

(34) The common character of them is that, member classifier is generated by disturbing feature subspace and model parameters, and the finial decision is made by the majority voting procedure.

(35) The LS channel estimation of OFDM systems can be viewed as a noisy observation of the true channel frequency response, so the noise component can be compressed through subspace projecting.

(36) The algorithm projects the LC- MVB weight vector onto the signal subspace, thus the effect of the noise subspace on the weight vector is reduced.

(37) Aiming at the performance of MUSIC algorithm decreases in DOA estimation with snapshot deficient scenario, a new method based on weighted signal subspace projection is proposed.

(38) Compared with a system performance monitoring based on characteristic subspace, the improved PCA is more effective.

(39) The energy density of the 4-dimensional spacetime is supposed to be dominated by incoherent radiation and the energy-momentum tensor of the internal subspace is a step function.

(40) We researched the subspace eigenvalue decomposition and weighted subspace fitting techniques in the beam space.

(41) Based on online recursive closed - loop subspace identification, a model predictive damping controller design strategy was proposed.

(42) A new supervised kernel subspace method for face recognition was proposed.

(43) The GIP consists of formation of a matrix equivalent to tolerance disturbance, determination of an optimal information subspace, and inverse projection.

(44) A new approach is presented of the eigen-structure subspace algorithms, the problem of ambiguous estimation in the original algorithm is solved and array architecture is optimized.

(45) In this paper, we have discussed root subspace decomposition of linear space, and for the linear space have decomposed direct sum of root subspace (), a primary proof is given.

(46) In order to improve the convergence rate of the dynamic condensation method, a new dynamic condensation method based on matrix power accelerated subspace iteration method is developed in this paper.

(47) Recognizing small handwritten character set with this new method and constructing an integrated reorganization system with subspace classifier and BP classifier are the main objects in this paper.

(48) Tellegen's theorem in various forms is derived by the orthogonality relation between the current subspace and voltage subspace.

(49) A new recursive subspace identification algorithm is proposed for the recursive estimation of state space model of linear time-varying systems.

(50) Combining the matrix power accelerated subspace iteration method with the shift technique, this paper presents a novel structural dynamic condensation method.

(51) Since the wavelets possess symmetry and interpolation, the sampling theorem on approximation subspace is established easily.

(52) The system order is decided by non-zerosingular values of the observation matrix in the subspace state space systemidentification method.

(53) In addition, some concise results are obtained by matrix representation of the orthogonal complement and injection of vectors on the subspace.

(54) High - dimensional data mining faces the challenges of distributed data sparsity and overlapping feature subspace.

(55) PCA approach partitions the measurement space into principal component subspace ( PCS ) and residual subspace ( RS ).

(56) Maximum likelihood performs a nonlinear dimensionality reduction, choosing permutations that compact the permuted image vectors into a volumetrically minimal subspace.

(57) By analysis the distribute of the data in subspace, the speech and non - speech can be detected.

(58) The algorithm is based on the subspace decomposition technique. The signal subspace is separates from the noise subspace by making use of the orthogonality between them.

(59) In the linear space with descending chain condition of subspaces, every subspace can be written as finite intersection of maxmin subspaces.

(60) This paper presents a method of coherent signal subspace based wideband optimal beamforming for acoustic vector-sensor (AVS) array.

(61) Definition 2 : Given two vector spaces, if, then V 1 is called a subspace of v 2.

(62) As a result, the features of training samples and testing sample are got by projecting them on the subspace spanned by optimal base vectors.

(63) Simulations show that this algorithm has equivalent performance but simpler computation as compared with the multiuser detection algorithm based on subspace algorithm.