Theory And Application Of High-Dimension Biomimetic Information Geometric

Based on human cognition, geometry theory of high-dimensional biomimetic information is not only a kind of machine learning theory, but also an important guidance method for information processing. Following aspects of the theory are discussed in this paper, and some useful results are obtained.Geometry theory of high-dimensional biomimetic information and its calculation start from the concept of geometrical figures, and describe the sub-space with a point set in space. Complex computation in high-dimensional space is conducted by means of simple Euclidean geometry iterative operations. Although some successful cases have been made, the advantages of axiomatic system in geometry are not involved. With the introducing the geometric linear algebra, the author systematically describes the high-dimensional geometry and establishes a self-consistent axioms system.The multi-weight neuron model based on the geometry theory of high-dimensional biomimetic information is one of the important fruits of the Biomimetic Pattern Recognition. A new algorithm about multi-weight neuron model is presented based on the review of main results of artificial neural network, and then it is applied to speaker recognition successfully. Comparing it with the well-known speaker recognition algorithm demonstrate the effectiveness of our algorithm.Face recognition is an attractive issue in the machine vision field. Based on the review of face recognition in detail, the author combines the kernel method, proposes a new algorithm based on kernel smallest ball for face recognition, the experimental results demonstrate the effectiveness of the algorithm. Gabor filter gives the best resolution in spatial domain and frequency. It is beneficial for extracting the image texture futures and concerned in face recognition area widely. The theory of Gabor filter and its relevant papers are summarized in this paper. Combined with the theory of biomimetic patter recognition, a minimum spanning tree algorithms is proposed in this paper. This algorithm is applied in the face recognition experiment in the extreme case of single training sample in each class. In addition, the face recognition in illumination changes is deeply studied in this paper, and its effectiveness is proved. Log-Gabor filter can maximize space location. A face recognition algorithm based on the Log-Gabor filter of binary transform is proposed in this paper. The storage and computing efficiency is improved. The new algorithms is more effective than the benchmark algorithms in recognizing faces with different positions, lights, expressions, accessories and distances in the JDL-A face database.With the innovation of computer hardware and the progress of machine learning, more and more researchers are attracted by the technology of content-based image retrieval. On the basis of the high-dimensional biomimetic information geometry, the author studies the image retrieval by global features and the regional features. A prototype system of image retrieval is provided. A retrieval result similar with SIMPLIcity system or better is obtained on the COREL subset database. Combining with the relevance feedback technique, the author uses liner discrimination analysis for dimensional reduction, and the low-dimensional feature obtained can better reflect the high-level semantic information and further reduce the gap between low-level vision features and high-level semantic.