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(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,(www.Sentencedict.com) 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.