Dissertation > Excellent graduate degree dissertation topics show

Application of Adaptive Principal Component Extraction to Gene Expression Data

Author: YangShengQi
Tutor: ZhangJunYing
School: Xi'an University of Electronic Science and Technology
Course: Applied Computer Technology
Keywords: Feature Extraction Principal Component Analysis Adaptive principal component extraction algorithm Artificial Neural Networks Gene expression data
CLC: TP399-C8
Type: Master's thesis
Year: 2008
Downloads: 34
Quote: 0
Read: Download Dissertation


Has been the principal component analysis (PCA) is a highly scientific research scholars pay close attention , it can find a reversible orthogonal transformation , the original high -dimensional data is projected onto the lower-dimensional data space , and retain the main features of the data . PCA has been widely used in many fields of modern signal processing , such as data compression , feature extraction , pattern recognition , digital communications , and computer vision . However , the traditional PCA method based on KL transform data autocorrelation matrix eigenvalues ??and vector calculation , but such a large number of matrix operations programmed some difficulty , increase the complexity of the algorithm . This paper will combine the PCA method and artificial neural network , a multi-master extraction algorithm based on neural network , focusing on adaptive principal component extraction (APEX) neural network algorithm . APEX algorithm to take advantage of unsupervised adaptive neural network parallel computing direct extraction of principal components , thus greatly improving the speed of feature extraction . This article uses a Gaussian distribution of artificial simulation data and high- wiki gene expression data , the the APEX algorithm with traditional PCA algorithm based on KL transform various aspects of performance comparison . And for the first time the APEX neural network algorithm for gene expression data processing , through comparative experiments on the Yeast and NCI64 two kinds of gene expression data show that the the APEX algorithm and the traditional principal component extraction algorithm based on KL transform compared with significantly faster operation speed. In addition, according to the principal components of the original gene expression data reconstruction, Expand pave the way for the next step in the subject .

Related Dissertations

  1. High Speed Frequency Measurment and Non-Linearity Correction of Frequency Modulated Capacitive Displacement Sensor,TH822
  2. Research on Automatic Detection Algorithm for Substructure Distress of Highway Pavement Based on SVM,U418.6
  3. ISAR Imaging Simulation of Space Targets and Target Recognition Based on ISAR Images,TN957.52
  4. Research on Feature Extraction and Classification of Pulse Waveform for Cholecystitis and Nephrotic Syndrome Diagnosis,TP391.41
  5. Application of Q-Learning in the Content-Based Image Retrieval Technology,TP391.41
  6. Research on Transductive Support Vector Machine and Its Application in Image Retrieval,TP391.41
  7. Research on Feature Extraction and Classification of Tongue Shape and Tooth-Marked Tongue in TCM Tongue Diagnosis,TP391.41
  8. Research on Visual Measurement for Spacecraft Rendezvous and Approach,TP391.41
  9. Research on the Image Real-Time Acquisition, Storage and Image Processing System,TP391.41
  10. Feature Extraction, Selection and Combination in Lipreading,TP391.41
  11. Multi-currency Notes Technology Research and Implementation,TP391.41
  12. The Research on Paper Currency Classification Method Based on Harr-Like Feature and Minimal Ball Including Samples,TP391.41
  13. Pavement Distress Recognition Based on Image,TP391.41
  14. Research on Visual Detection and Tracking of Mobile Robots,TP242.62
  15. Research on Fusion Algorithm of Hyper Spectral and High Spatial Resolution Remote Sensing Image,TP751
  16. Application of Improved Principal Component Analysis Algorithm in Course Construction,G642.4
  17. An Approach for Identifying a Plant Resistance Gene Based on the Random Forest,Q943
  18. Tobacco Diseases Auto-Recognition Research Based on Image Processing Technology,S435.72
  19. Research on Nondestructive Detection Technology for External Qualities of Papayas Based-on Vision,S667.9
  20. Research on Identification System of Cashmere and Wool Fiber,TS101.921
  21. Comparison of Gene Expression Data Cluster Methods and Gene Network Construction for Phytophthora Sojae Genes,S435.651

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > In other aspects of the application
© 2012 www.DissertationTopic.Net  Mobile