Extensive simulations were carried out on Fast ICA and proposed ICA with two speech mixes each sampled at 16 KHz.5.1 Results of recorded speech mixes The speech signal is a super Gaussian signal which has a positive kurtosis value. The spiky probability density function with heavy tails is the important property of random variables of super-Gaussian signals while sub-Gaussian signals have a flat probability density function. Most real-world signals such as engine noise are superGaussian in nature. The experimental results of the recorded speech signals are shown in Fig.4 (a) -Fig 4 (d). Fig.4(a) and Fig.4(b) shows a mixture of two recorded speech signals each sampled at 4.8 KHz. Fig.4(c) and Fig.4(d) show the extracted independent male and female vocal components obtained through the proposed ICA algorithm. Since the defined algorithm should be able to handle real-sized instances, 80,000 samples are taken for processing.5.1 Convergence AnalysisConvergence analysis is performed from the simulation results obtained from NCsim Tool v10. Convergence speed represents the time it takes for each of the algorithms to reach convergence. It is obtained when a vector w(k) and its updated vector w(k+1) point in the same direction. The proposed ICA requires 11 iterations and the fast ICA requires 18 iterations to achieve convergence and separate two recorded speech mixtures. Table 1 clearly illustrates the convergence performance in terms of number of iterations. Convergence... at the center of the article... Component analysis. IEEE Trans. Industrial Electronics, 54: 548-558. DOI: 10.1109/TIE.2006.885491[20]. Kim, C.M., H.M.. Park, T. Kim, Y. K. Choi, and S. Y. Lee, (2003). FPGA implementation of the ICA algorithm for blind signal separation and adaptive noise cancellation. IEEE Trans. Neural Network, 14: 1038-1046. PMID: 18244558[21]. Kuo-Kai Shyu, Ming-Huan Lee, Yu-Te Wu and Po-Lei Lee. (2008) Implementation of FastICA pipeline on FPGA for real-time blind source separation. IEEE Trans. On Neural Networks, Vol. 19, no. 6 PMID18541497[22]. Dinesh, P., N. Das, and A. Routray, (2011). Fast-ICA implementation: A performance-based comparison between floating-point and fixed-point DSP platforms. Measuring skis. Revelation, 11: 119-18. http://connection.ebscohost.com/c/articles/69721126/implementation-fast-ica-performance-based-comparison-between-floating-point-fixed-point-dsp-platform