Wavelet Transform Based Estimation of 1 Dimensional Signal
Koteswara Rao Mallaparapu1, K.V.Ramarao2, Shaik Masthan3
1Koteswara Rao Mallaparapu*, Assistant Professor of ECE, CIET, Guntur, AP, India.
2Dr.K.V.Ramarao, Associate Professor of ECE, CIET, Guntur, AP, India.
3Shaik Masthan, Assistant Professor of ECE, CIET, Guntur, AP, India.
Manuscript received on January 15, 2020. | Revised Manuscript received on January 27, 2020. | Manuscript published on February 10, 2020. | PP: 1264-1267 | Volume-9 Issue-4, February 2020. | Retrieval Number: D9063019420/2020©BEIESP | DOI: 10.35940/ijitee.D9063.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The key idea of this manuscript is denoising of noisy biological signals. For this wavelet thresholding technique is suggested. To eliminate the noise existing in the signal, mixed thresholding function is considered which is the median of Hard, Soft and Garrote functions. The mixed thresholding function is applied by degraded white gaussian noise Electrocardiogram signal. Two methods that are used to calculate the threshold value is FDR technique and Visu shrink technique. The outcomes of mixed functions are compared with remaining functions using Signal to Noise Ratio (SNR) and Mean Square Error (MSE). It is obvious that the mixed function performs superior than remaining functions using Visu shrink technique and performs better than only Hard function using FDR technique.
Keywords: It is Obvious that the Mixed Function Performs Superior than Remaining Functions using Visu Shrink Technique and Performs Better than Only Hard Function using FDR Technique.
Scope of the Article: Routing, Switching and Addressing Techniques