Segmentation of composite signal into harmonic Fourier expansion using genetic algorithm

A composite signal is generally composed of multiple signals with various frequencies and amplitudes. Fourier series expansion is one of the examples of such decomposition in sine and cosine components. The finding of coefficients value is a tedious job. Approximate decomposition of composite signal with greater accuracy is possible using optimization. In this paper, a genetic algorithm-based optimization is proposed for such decomposition. Genetic algorithm is devised to mimic the natural selection process of evolution and provides an elegant way to arrive at an optimal solution. The problem that is dealt with in this paper is to find the coefficients of a Fourier expansion for best fitting after iteration of multiple generations. Different combinations of various crossovers and mutations are implemented. The results of the different combinations are analysed with different selection techniques.