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Particle Filturing

于 2020-10-26 发布文件大小:20KB

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下载积分: 1 下载次数: 23

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代码说明：

粒子群滤波算法及改进算法代码，包含代码说明(Particle swarm optimization algorithm and improved algorithm code, including code description)

文件列表：

粒子滤波\data.txt, 1393 , 2010-01-07
粒子滤波\hist2.m, 2433 , 2009-06-03
粒子滤波\histgram1.m, 2031 , 2009-06-06
粒子滤波\initial1.m, 1298 , 2009-06-06
粒子滤波\Observe_and_Estimate.m, 2226 , 2009-06-06
粒子滤波\Propagation.m, 1711 , 2009-01-04
粒子滤波\Select.m, 706 , 2006-09-06
粒子滤波\show2.fig, 6964 , 2007-11-11
粒子滤波\show2.m, 19044 , 2009-06-02
粒子滤波\tracker.m, 2725 , 2009-05-19
粒子滤波\tracker1.m, 3013 , 2010-10-08
粒子滤波\tracker改动.m, 3079 , 2009-06-03
粒子滤波\weight.m, 744 , 2009-06-06
粒子滤波, 0 , 2010-10-13

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code for creating a histogram equalization graph in matlab it convert it first to histogram then perform histogram equlization

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RLS
仿真对象如下：其中， v( k )为服从N (0,1) 分布的白噪声。输入信号u ( k) 采用M 序列，幅度为 1。M 序列由 9 级移位寄存器产生，x(i)=x(i-4)⊕x(i-9)。选择如下辨识模型：加权阵取Λ = I。衰减因子β = 0.98，数据长度 L = 402。辨识结果与理论值比较，基本相同。辨识结果可信 (he simulation object is as follows: among them, v (k) to obey N (0, 1) distribution of white noise. The input signal u (k) using M sequence, amplitude is 1. M sequence by 9 level shift register generation, x (I) = x (I- 4) ⊕ x (I- 9). Choose the identification model: weighted array take Λ = I. Attenuation factor β = 0.98, the data length L = 402. Identify the theoretical calculation and comparison, basically the same. Identification results are reliable)

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