tailieunhanh - Báo cáo hóa học: " Research Article Lossless Compression Schemes for ECG Signals Using Neural Network Predictors"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Lossless Compression Schemes for ECG Signals Using Neural Network Predictors | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 35641 20 pages doi 2007 35641 Research Article Lossless Compression Schemes for ECG Signals Using Neural Network Predictors R. Kannan and C. Eswaran Center for Multimedia Computing Faculty of Information Technology Multimedia University Cyberjaya 63100 Malaysia Received 24 May 2006 Revised 22 November 2006 Accepted 11 March 2007 Recommended by William Allan Sandham This paper presents lossless compression schemes for ECG signals based on neural network predictors and entropy encoders. Decorrelation is achieved by nonlinear prediction in the first stage and encoding of the residues is done by using lossless entropy encoders in the second stage. Different types of lossless encoders such as Huffman arithmetic and runlength encoders are used. The performances of the proposed neural network predictor-based compression schemes are evaluated using standard distortion and compression efficiency measures. Selected records from MIT-BIH arrhythmia database are used for performance evaluation. The proposed compression schemes are compared with linear predictor-based compression schemes and it is shown that about 11 improvement in compression efficiency can be achieved for neural network predictor-based schemes with the same quality and similar setup. They are also compared with other known ECG compression methods and the experimental results show that superior performances in terms of the distortion parameters of the reconstructed signals can be achieved with the proposed schemes. Copyright 2007 R. Kannan and C. Eswaran. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Any signal compression algorithm should strive to achieve greater compression ratio and better signal quality without .