Overcomplete discrete wavelet transform based respiratory sound discrimination with feature and decision level fusion
暂无分享,去创建一个
[1] David G. Stork,et al. Pattern Classification , 1973 .
[2] Stan Davis,et al. Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Se , 1980 .
[3] R. Baughman,et al. Lung sound analysis for continuous evaluation of airflow obstruction in asthma. , 1985, Chest.
[4] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[5] H Hermansky,et al. Perceptual linear predictive (PLP) analysis of speech. , 1990, The Journal of the Acoustical Society of America.
[6] Geoffrey E. Hinton,et al. Adaptive Mixtures of Local Experts , 1991, Neural Computation.
[7] John G. Proakis,et al. Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .
[8] Harris Drucker,et al. Boosting and Other Ensemble Methods , 1994, Neural Computation.
[9] P. Piirilä,et al. Crackles: recording, analysis and clinical significance. , 1995, The European respiratory journal.
[10] Noam Gavriely,et al. Breath Sounds Methodology , 1995 .
[11] Lalu Mansinha,et al. Localization of the complex spectrum: the S transform , 1996, IEEE Trans. Signal Process..
[12] B Sankur,et al. Multiresolution biological transient extraction applied to respiratory crackles. , 1996, Computers in biology and medicine.
[13] Kevin W. Bowyer,et al. Combination of Multiple Classifiers Using Local Accuracy Estimates , 1997, IEEE Trans. Pattern Anal. Mach. Intell..
[14] H. Pasterkamp,et al. Respiratory sounds. Advances beyond the stethoscope. , 1997, American journal of respiratory and critical care medicine.
[15] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[16] A. Dittmar,et al. The relationship between normal lung sounds, age, and gender. , 2000, American journal of respiratory and critical care medicine.
[17] C. Chui,et al. Compactly supported tight frames associated with refinable functions , 2000 .
[18] James C. Bezdek,et al. Decision templates for multiple classifier fusion: an experimental comparison , 2001, Pattern Recognit..
[19] I. Selesnick. The Double Density DWT , 2001 .
[20] Ethem Alpaydin,et al. Introduction to machine learning , 2004, Adaptive computation and machine learning.
[21] N. Malmurugan,et al. Neural classification of lung sounds using wavelet coefficients , 2004, Comput. Biol. Medicine.
[22] Y.P. Kahya,et al. A Multi-Channel Device for Respiratory Sound Data Acquisition and Transient Detection , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.
[23] Hüseyin Polat,et al. Combining Neural Network and Genetic Algorithm for Prediction of Lung Sounds , 2005, Journal of Medical Systems.
[24] Richard Baraniuk,et al. The Dual-tree Complex Wavelet Transform , 2007 .
[25] R. Polikar,et al. Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.
[26] Chee Kheong Siew,et al. Extreme learning machine: Theory and applications , 2006, Neurocomputing.
[27] Philip S. Yu,et al. Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.
[28] E. Andrès,et al. Analysis of Respiratory Sounds: State of the Art , 2008, Clinical medicine. Circulatory, respiratory and pulmonary medicine.
[29] Stephen R. Marsland,et al. Machine Learning - An Algorithmic Perspective , 2009, Chapman and Hall / CRC machine learning and pattern recognition series.
[30] Ivan W. Selesnick,et al. Frequency-Domain Design of Overcomplete Rational-Dilation Wavelet Transforms , 2009, IEEE Transactions on Signal Processing.
[31] Ali Abbas,et al. An Automated Computerized Auscultation and Diagnostic System for Pulmonary Diseases , 2010, Journal of Medical Systems.
[32] Katsuya Yamauchi,et al. Classification between normal and abnormal respiratory sounds based on maximum likelihood approach , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[33] Ivan W. Selesnick,et al. Oscillatory plus transient signal decomposition using overcomplete rational-dilation wavelet transforms , 2009, Optical Engineering + Applications.
[34] Leontios J. Hadjileontiadis,et al. Analysis of Wheezes Using Wavelet Higher Order Spectral Features , 2010, IEEE Transactions on Biomedical Engineering.
[35] P. Mayorga,et al. Acoustics based assessment of respiratory diseases using GMM classification , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[36] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[37] Nizamettin Aydin,et al. Pulmonary crackle detection using time-frequency and time-scale analysis , 2013, Digit. Signal Process..
[38] Rajkumar Palaniappan,et al. Machine learning in lung sound analysis: a systematic review , 2013 .
[39] A. Bohadana,et al. Fundamentals of lung auscultation. , 2014, The New England journal of medicine.
[40] Yasemin P. Kahya,et al. Respiratory sound classification using perceptual linear prediction features for healthy - Pathological diagnosis , 2014, 2014 18th National Biomedical Engineering Meeting.
[41] Kenneth Sundaraj,et al. A telemedicine tool to detect pulmonary pathology using computerized pulmonary acoustic signal analysis , 2015, Appl. Soft Comput..
[42] Goutam Saha,et al. Lung sound classification using cepstral-based statistical features , 2016, Comput. Biol. Medicine.
[43] J. Geoffrey Chase,et al. A proof of concept study of acoustic sensing of lung recruitment during mechanical ventilation , 2017, Biomed. Signal Process. Control..