Search - Recursion algorithm

Search - Recursion algorithm - List

[AI-NN-PR] x DL : 0: This derivation of the normalised least mean square algorithm is based on Farhang- Boroujeny 1999, pp.172-175, and Diniz 1997, pp 150-3. To derive the NLMS algorithm we consider the standard LMS recursion, for which we select a variable step size parameter, μ(n). This parameter is selected so that the error value , e+(n), will be
Date : 2026-01-08 Size : 1kb User : bahtiar
[AI-NN-PR] not-recursive-realized DL : 0: 该程序是分段函数： akm(m,n){ n+1 m =0 akm(m-1,1) m!=0,n=0 akm(m-1),(akm(m,n-1)) m!=0,n!=0 实现递归和非递归的算法非递归算法可能使计算时间减少-The program is piecewise function: Akm (m, n) { N+ 1 m = 0 Akm (m-1, 1) m! = 0, n = 0 Akm (m-1) (akm (m, n-1)) m! = 0, n.= 0 Realize the recursive and the recursion algorithm The recursion algorithm may make computing time reduced
Date : 2026-01-08 Size : 1kb User :
[AI-NN-PR] RFF DL : 1: 辨识模型与遗忘因子法所用模型相同，其中， 0 ≤μ≤1为遗忘因子，此处取0.98。数据长度L=402。一次算法和递推算法结果基本一致，但递推算法可以实现在线实时辨识，而且可以减少计算量和存储量。-Identification model and forgetting factor method used the same model, among them, 0 or less or less 1 μ for forgetting factor, here take 0.98. Data length L = 402. A algorithm and recursion algorithm results are basically the same, but the recursion algorithm can realize the real-time online identification, and can reduce the computation time and memory requirement greatly.
Date : 2026-01-08 Size : 1kb User : 张鹏
[AI-NN-PR] RELS DL : 0: 增广最小二乘的递推算法对应的噪声模型为滑动平均噪声，扩充了参数向量和数据向量H（k）的维数，把噪声模型的辨识同时考虑进去。最小二乘法只能获得过程模型的参数估计，而增广最小二乘法同时又能获得噪声模型的参数估计，若噪声模型为平均滑动模型，，则只能用RELS算法才能获得无偏估计。当数据长度较大时，辨识精度低于极大似然法。-Augmented least squares of recursion algorithm corresponding noise model for moving average noise, expanded parameter vector and data vector H (k) of the dimension, the noise model identification and at the same time into consideration. Least square method can only obtain process model parameter estimation, and augmented least squares method at the same time can obtain noise model parameter estimation, if noise model for the average sliding model,, it can only use RELS algorithm to obtain unbiased estimation. When the data length is bigger, the identification accuracy is lower than maximum likelihood method.
Date : 2026-01-08 Size : 1kb User : 张鹏
[AI-NN-PR] introduction-of-adp DL : 1: 自适应动态规划介绍。一种求解动态规划方法HJB方程的自学习控制算法，称其为自适应动态规划算法。所提的算法可以用来解决未知离散时间非线性系统的最优控制问题，同时给出了该控制算法的收敛性证明。算法的实现用到了三个神经网络，在递推的每一步分别用来近似性能指标函数、最优控制律和未知非线性系统。-Adaptive Dynamic Programming introduction. Dynamic programming method for solving the HJB equation self-learning control algorithm, called adaptive dynamic programming algorithm. The proposed algorithm can be used to solve the unknown discrete-time nonlinear optimal control problems, and gives the control algorithm convergence proof. Algorithm uses three neural networks, each step of the recursion are used to approximate the performance index function, optimal control law and unknown nonlinear systems.
Date : 2026-01-08 Size : 950kb User : chenyi