Abstract: One-unit ICA-R is an efficient method utilizing prior information to extract an expected source signal.Kurtosis is a classical measure of non-Gaussianity of random variable.Based on constrained independent component analysis，a fast algorithm for one-unit ICA-R is proposed when absolute value of kurtosis is considered as contrast function in this paper.A better initial value is provided to accelerate convergence based on convergent characteristic of the algorithm.At last，computer simulations verify the validity of the proposed algorithm and indicate that the better initial value can improve convergence indeed.

Key words: kurtosis, contrast function, Independent Component Analysis with Reference（ICA-R）, Signal to Noise Ratio（SNR）

摘要： 一单元参考独立成分分析是一种有效的利用先验信息抽取一个期望源信号的方法。峭度是随机变量非高斯性的一个经典度量。基于约束独立成分分析理论，以峭度的绝对值为对比函数推导出一种快速一单元ICA-R算法。并针对该算法的收敛特点，给出一个优选初值去提升算法的收敛速度。最后，通过计算机模拟实验验证了该算法的有效性，同时所给优选初值加快算法收敛的性能也得到验证。

关键词: 峭度, 对比函数, 参考独立成分分析, 信噪比