1 And an orthonormal basis of the kernel feature space is constructed.

2 Then, it establishes a feature space model, uses a similarity function to choose the optimal feature space, which simplifies the tracking difficulty and reduces the number of features.

3 Concepts of Primary Feature Field and Primary Feature Space are defined,(www.Sentencedict.com) and factor of Primary Feature Word is introduced to the traditional weighting schema to enhance the system performance.

4 CDCPM describes the feature space of model by center distance normal distribution (CDN), and simplifies and improves the HMM efficiently by getting rid of the state transition probability matrix A.

5 Then it studies segment color images in the feature space to choose a method which bases on non-supervise, and the experiments have testified the efficiency.

6 Finally, the dimensional reduction and selection of feature space for ultrasonic and the optimum feature subset have been successfully implemented using the method mentioned above.

7 This is the reason that our rolling pumps feature space saving and high flow .

8 A new feature space transformation algorithm in color image is presented.

9 And relations between Contact Feature Space and tools'surface meshes are established.

10 The optimum selection of bands and its combinations in remote sensing classification and the method for expanding feature space are presented.

11 We propose a multi-resolution classification strategy based on the partition of feature space.

12 Moreover, a new visual control scheme based on artificial neural network is designed, and the visual tracking problem is converted into a servo problem in image feature space.

13 This algorithm is a combination of kernel trick with the covering algorithm, and is used to extract the support vectors in feature space.

14 For each bone X ray image, the distance from its features to the two prototypes in feature space is computed to provide an objective judgement on the degree of osteoporosis.

15 In this algorithm the classification of samples in the critical zone is decided by the voting of K-NN set in the feature space and the sample space.

16 On the basis of this model, the concept of Contact Feature Space is proposed.

17 High accuracy DEMs is an important data in study of soil erosion and terrain feature space analysis.

18 MFCC uses intermediate clustering results in one type of feature space to help the selection in other types of feature spaces.

19 After training samples and test samples are respectively projected towards the fusion feature space, recognition features are accordingly gained.

20 The kernel method improves the optimization of the example features and transforms the nonlinear learning problems to linear learning problems by mapping the samples from input space to feature space.

21 In this paper, a novel fuzzy membership function model is presented based on the feature space.

22 Moreover, in IDDT diagnosis, the conception of fault feature curve and feature space is proposed to diagnose the fault in the analog and mixed-signal circuit.

23 Its mathematical basis are topological analysis of sample set in the high dimensional feature space, therefore it is also called the Topological Pattern Recognition.

24 This paper presents a multiclass neural network classifier to learn disjunctive fuzzy information in the feature space.

25 In the field of human face tracking, we contrast several main similarity methods nowadays, and adopt a method of human face tracking based on feature space model.

26 In the meanwhile, the two feature sub-spaces from PCA and LDA are fused, and the fusion feature space is acquired.