A novel idea,called the optimal shape subspace （OSS） is first proposed for optimizing active shape model （ASM） search.It is constructed from the principal shape subspace and the principal shape variance subspace.It allows the reconstructed shape to vary more than that reconstructed in the standard ASM shape space,hence it is more expressive in representing shapes in real life.Then a cost function is developed,based on a study on the search process.An optimal searching method using the feedback information provided by the evaluation cost is proposed to improve the performance of ASM alignment.Experimental results show that the proposed OSS can offer the maximum shape variation with reserving the principal information and a unique local optimal shape is acquired after optimal searching.The combination of OSS and optimal searching can improve the ASM performance greatly.
提出一种适用于正交频分复用(Orthogonal frequency division multiplexing,OFDM)系统的低复杂度信道时域响应估计算法。在发送端,算法基于最小均方误差(Mean-square error,MSE)准则以及给定的导频分布对导频功率及相位进行设计;在接收端,算法直接对接收到的导频符号进行求和,通过对求和结果进行简单加权后得到信道时域响应的估计。由于该算法在估计信道时只需进行很少量的复数乘法运算,因此接收端的计算复杂度非常低。理论分析与仿真结果表明,当信道时不变或慢时变时,该算法具有较小的估计均方误差。
