TY - JFULL AU - Lei Lei and Chao Wang and Xin Liu PY - 2013/10/ TI - Discrete Wavelet Transform Decomposition Level Determination Exploiting Sparseness Measurement T2 - International Journal of Electrical and Computer Engineering SP - 1181 EP - 1185 VL - 7 SN - 1307-6892 UR - https://publications.waset.org/pdf/16666 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 81, 2013 N2 - Discrete wavelet transform (DWT) has been widely adopted in biomedical signal processing for denoising, compression and so on. Choosing a suitable decomposition level (DL) in DWT is of paramount importance to its performance. In this paper, we propose to exploit sparseness of the transformed signals to determine the appropriate DL. Simulation results have shown that the sparseness of transformed signals after DWT increases with the increasing DLs. Additional Monte-Carlo simulation results have verified the effectiveness of sparseness measure in determining the DL. ER -