**Figure 2.**

*Detailed coefficients of the EEG signal.*

*EEG Signal Denoising Using Haar Transform and Maximal Overlap Discrete Wavelet… DOI: http://dx.doi.org/10.5772/intechopen.93180*

#### **Figure 3.**

*Maximal overlap discrete wavelet transform.*


#### **Table 1.**

*Parameters of the signal.*


**Table 2.**

*Parameters of MODWT using Daubechies Extremal phase wavelet.*

### **5. Conclusion**

In this paper, EEG signal has been analyzed with the help of transformation techniques like Haar Transform and with Maximal Overlap Discrete Wavelet Transform for the analysis of Epilepsy. It has been observed that the mean of the filtered signal and the input signal was approximately same after applying the transformations. These transforms are the processing algorithms to filter the noisy coefficients of the original signal. The structure of the signal should be same after the application of the algorithms especially in the case of biomedical applications where it has been achieved with the help of these Haar and Maximal Overlap Discrete Wavelet Transform (MODWT) for the identification of Epilepsy.
