Cycle frequency-based blind beamforming shows the performance degradation due to cfe ( cyclic frequency error ) . an improved algorithm is presented in literature 6, which adopting forgetting factor in estimation cyclic correlation matrix would largely depress the sensitivity of cab to cyclic frequency error . by using this method, the improved algorithms of the c-cab and ecab algorithms are presented in this dissertation 针对基于循环频率的盲波束形成算法对循环频率误差cfe(cyclicfrequencyerror)很敏感而导致算法性能下降的情况,参照文献[6]提出的遗忘因子cab算法,提出了c-cab算法以及基于特征空间的盲波束形成算法(ecab)的改进算法。
On the basis of the traditional time-series method, an improved method is obtained by inducting the recursive forgetting factor least square method ( rffls ), which brings about the real-time online prediction and smoothes away the problem of random severe interferences and great uncertainty in the real-time prediction of short-term traffic flow 在传统的时间序列方法基础上引入带遗忘因子的最小二乘递推算法得到改进算法,实现了实时在线预测,解决了短时交通流量实时预测中存在的随机干扰因素影响大、不确定性强的问题。