This paper proposes a Gaussian mixture model(GMM)-based music discrimination system for FM broadcasting. The objective of the system is automatically archiving music signals from audio broadcasting programs that are normally mixed with human voices, music songs, commercial musics, and other sounds. To improve the system performance, make it more robust and to accurately cut the starting/ending-point of the recording, we also added a post-processing module. Experimental results on various input signals of FM radio programs under PC environments show excellent performance of the proposed system. The fixed-point simulation shows the same results under 3MIPS computational power.
This paper presents an efficient adaptive predistortion technique for compensation of linear and nonlinear distortion caused by high-power amplifier with memory in satellite communication channels. The previous adaptive predistortion 'techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In this paper, the memoryless HPA preceded by a linear dynamic system is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter structured by the Hammestein model. An adaptive algorithm for adjusting the parameters of the predistorter is derived using the stochastic gradient method. The validity of the proposed approach is confirmed via computer simulation by applying it to
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