A new electrocardiogram(ECG) data compression method is presented.It employs a repeated coding.In this method beat templates are extracted from original signals according to the features of ECG.The data are divided in...A new electrocardiogram(ECG) data compression method is presented.It employs a repeated coding.In this method beat templates are extracted from original signals according to the features of ECG.The data are divided into three parts:beat template,residual and position parameter.The three separate parts are first encoded with LADT,and then use the lossless entropy encoding to maintain a low level of reconstructed waveform distortion.The entropy encoding based on Huffman encoding is employed here as an example.Selections from the MIT BIH arrhythmia database,show that there is substantial improvement in compression ratio (CR) over other single and simple compression methods for comparable percent root mean square difference(PRD).展开更多
Huffman[Huffman(1952)]encoding is one of the most known compression algorithms.In its basic use,only one encoding is given for the same letter in text to compress.In this paper,a text compression algorithm that is bas...Huffman[Huffman(1952)]encoding is one of the most known compression algorithms.In its basic use,only one encoding is given for the same letter in text to compress.In this paper,a text compression algorithm that is based on Huffman encoding is proposed.Huffman encoding is used to give different encodings for the same letter depending on the prefix preceding it in the word.A deterministic finite automaton(DFA)that recognizes the words of the text is constructed.This DFA records the frequencies for letters that label the transitions.Every state will correspond to one of the prefixes of the words of the text.For every state,a different Huffman encoding is defined for the letters that label the transitions leaving that state.These Huffman encodings are then used to encode the letters of the words in the text.This algorithm was implemented and experimental study showed significant reduction in compression ratio over the basic Huffman encoding.However,more time is needed to construct these codes.展开更多
文摘A new electrocardiogram(ECG) data compression method is presented.It employs a repeated coding.In this method beat templates are extracted from original signals according to the features of ECG.The data are divided into three parts:beat template,residual and position parameter.The three separate parts are first encoded with LADT,and then use the lossless entropy encoding to maintain a low level of reconstructed waveform distortion.The entropy encoding based on Huffman encoding is employed here as an example.Selections from the MIT BIH arrhythmia database,show that there is substantial improvement in compression ratio (CR) over other single and simple compression methods for comparable percent root mean square difference(PRD).
文摘Huffman[Huffman(1952)]encoding is one of the most known compression algorithms.In its basic use,only one encoding is given for the same letter in text to compress.In this paper,a text compression algorithm that is based on Huffman encoding is proposed.Huffman encoding is used to give different encodings for the same letter depending on the prefix preceding it in the word.A deterministic finite automaton(DFA)that recognizes the words of the text is constructed.This DFA records the frequencies for letters that label the transitions.Every state will correspond to one of the prefixes of the words of the text.For every state,a different Huffman encoding is defined for the letters that label the transitions leaving that state.These Huffman encodings are then used to encode the letters of the words in the text.This algorithm was implemented and experimental study showed significant reduction in compression ratio over the basic Huffman encoding.However,more time is needed to construct these codes.
