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Wavelet Theory: Applications of the Wavelet

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In this Chapter, continuous Haar wavelet functions base and spline base have been discussed. Haar wavelet approximations are used for solving of differential equations (DEs). The numerical solutions of ordinary differential equations (ODEs) and fractional differential equations (FrDEs) using Haar wavelet base and spline base have been discussed. Also, Haar wavelet base and collocation techniques are used to approximate the solution of Lane-Emden equation of fractional-order showing that the applicability and efficacy of Haar wavelet method. The numerical results have clearly shown the advantage and the efficiency of the techniques in terms of accuracy and computational time. Wavelet transform studied as a mathematical approach and the applications of wavelet transform in signal processing field have been discussed. The frequency content extracted by wavelet transform (WT) has been effectively used in revealing important features of 1D and 2D signals. This property proved very useful in speech and image recognition. Wavelet transform has been used for signal and image compression.
Title: Wavelet Theory: Applications of the Wavelet
Description:
In this Chapter, continuous Haar wavelet functions base and spline base have been discussed.
Haar wavelet approximations are used for solving of differential equations (DEs).
The numerical solutions of ordinary differential equations (ODEs) and fractional differential equations (FrDEs) using Haar wavelet base and spline base have been discussed.
Also, Haar wavelet base and collocation techniques are used to approximate the solution of Lane-Emden equation of fractional-order showing that the applicability and efficacy of Haar wavelet method.
The numerical results have clearly shown the advantage and the efficiency of the techniques in terms of accuracy and computational time.
Wavelet transform studied as a mathematical approach and the applications of wavelet transform in signal processing field have been discussed.
The frequency content extracted by wavelet transform (WT) has been effectively used in revealing important features of 1D and 2D signals.
This property proved very useful in speech and image recognition.
Wavelet transform has been used for signal and image compression.

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