遗忘因子(Forgetting Factor):遗忘因子通常用λ表示,取值范围一般在(0, 1]。它的作用就像是给过去的数据加了个“权重折扣”。当λ越接近1时,说明算法对过去的数据“记忆”越深刻,对新数据的重视程度相对较低,此时算法的跟踪能力较弱,但估计结果更平滑,抗噪声能力较强;而当λ越接近0时,算法会更看重新数据,对...
Keywords:dictionarylearning,sparsedecomposition,recursiveleastsquares(1RLS),forgettingfactor 近年来,信号稀疏分解已成为热点问题,并广泛 应用于压缩感知[】、图像处~[2-6]、信号去噪[6]、特征 提取[7-8]等领域.其中,JPEG2000编码标准的成功也 是由丁自然图像的小波系数具有稀疏性.然而,信号 ...
Priouret, "Performance analysis of the forgetting factor rls algorithm," International journal of adaptive control and signal processing, vol. 7, no. 6, pp. 525-538, 1993.L. Ljung L. Guo. "Performance Analysis of the For- getting Factor RLS Algorithm". Int. J. Adaptive Cont. Sig. ...
A new variable forgetting factor (VFF) RLS adaptive algorithm, namely gradient based VFF RLS algorithm (GVFF-RLS), is introduced in this paper. The control of the FF is based on the dynamic equation of the gradient of mse rather than on the gradient of instantaneous square error as in [...
'ForgettingFactor',0.95,'Constellation',pskmod(0:3,4,pi/4),'ReferenceTap',1, ... 'InitialInverseCorrelationMatrix',eye(5)*0.2) eqNew = comm.LinearEqualizer with properties: Algorithm: 'RLS' NumTaps: 5 ForgettingFactor: 0.9500 InitialInverseCorrelationMatrix: [5×5 double] Constellation: [...
内容简介:提出了用于智能天线自适应波束形成的梯度变遗忘因子RLS算法-GVFF-RLS(Gradient variable forgetting factor Recursive Least Square)算法,通过稳态性能分析及仿真模拟结果,此算法相比其它RLS算法有更快的跟踪能力和更小的均方误差(Mean Square Error),并且在低信噪比的条件下仍能保持良好的性能. ...
[22] Ding Feng, Chen Tongwen. Performance bounds of forgetting factor least-squares algorithms for time- varying systems with finite measurement data[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2005, 52(3): 555-566. ...
Forgetting factor (0 to 1)—RLS forgetting factor 1.0(default) | scalar in the range [0,1] Initial value of filter weights—Initial value of FIR filter weights 0(default) | vector Initial input variance estimate—Initial input covariance estimate ...
Variable forgetting factor; RLS algorithm; Cyclostationary signals; Smart antenna 1 引言 随着无线需求和服务的增长,提高无线通信的信道容量成为了急需解决的问题。解决这个的一个方法就是采用智能天线技术。而自适应形成算法是智能天线的关键技术,算法的好坏直接影响着智能天线的性能[1,2]。其中RLS以其快速的...
变遗忘因子策略:采用VFF-RLS(VariableForgettingFactor)在系统突变时自动降低λ值,某雷达跟踪系统测试表明响应延迟减少70% 稀疏系统优化:结合压缩感知理论,改进后的S-RLS算法在85%稀疏度信道估计中,计算复杂度降低至传统方法的35% 五、 信号建模:构造时变系统d(n)=θᵀ(n)φ(n)+v(n),其中θ(n)按随机游走模...