Yao-Shan Hung

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In this paper, a novel electrocardiogram (ECG) data compression method with full wavelet coefficients is proposed. Full wavelet coefficients involve a mean value in the termination level and the wavelet coefficients of all octaves. This new approach is based on the reversible round-off nonrecursive one-dimensional (1-D) discrete periodized wavelet transform(More)
Error propagation and word-length-growth are two intrinsic effects influencing the performance of wavelet-based ECG data compression methods. To overcome these influences, a non-recursive 1-D discrete periodized wavelet transform (1-D NRDPWT) and a reversible round-off linear transformation (RROLT) theorem are developed. The 1-D NRDPWT can resist truncation(More)
A modified two-dimensional (2-D) discrete periodized wavelet transform (DPWT) based on the homeomorphic high-pass filter and the 2-D operator correlation algorithm is developed in this paper. The advantages of this modified 2-D DPWT are that it can reduce the multiplication counts and the complexity of boundary data processing in comparison to other(More)
In the paper, a heuristic genetic algorithm for solving resource allocation problems is proposed. The resource allocation problems are to allocate resources to activities so that the fitness becomes as optimal as possible. The objective of this paper is to develop an efficient algorithm to solve resource allocation problems encountered in practice. Various(More)
In this paper, a novel ECG data compression method based on the reversible round-off non-recursive 1-D discrete periodized wavelet transform (1-D NRDPWT) is proposed. The reversible round-off 1-D NRDPWT can perform overall stages decomposition with minimum register word length and resist quantization error propagation. A non-linear word length reduction(More)
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