文件名称:burg
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用Burg算法估计AR模型参数，进而实现功率谱估计.
形参说明：
x——双精度实型一维数组，长度为n，存放随机序列。
n--整型变量,随机序列的长度。
p--整型变量,AR模型的阶数。
a--双精度实型一维数组，长度为(p十1)。存放AR模型的系数a(0),a(1),...,a(p)。
v--双精度实型指针,它指向预测误差功率，即AR模型激励白噪声的方差。
-with Burg algorithm estimates AR model parameters, thereby realizing the power spectrum estimation. - Participation : x -- double-precision real one-dimensional arrays, length n, storage random sequence. N -- integer variables, random sequence length. P -- integer variables, AR model of order. A -- double-precision real one-dimensional arrays, length (p 10). AR storage coefficient of a model (0), a (1 ),..., a (p). V -- double precision real-pointer, it forecast errors at power, AR model that inspired the white noise variance.
形参说明：
x——双精度实型一维数组，长度为n，存放随机序列。
n--整型变量,随机序列的长度。
p--整型变量,AR模型的阶数。
a--双精度实型一维数组，长度为(p十1)。存放AR模型的系数a(0),a(1),...,a(p)。
v--双精度实型指针,它指向预测误差功率，即AR模型激励白噪声的方差。
-with Burg algorithm estimates AR model parameters, thereby realizing the power spectrum estimation. - Participation : x -- double-precision real one-dimensional arrays, length n, storage random sequence. N -- integer variables, random sequence length. P -- integer variables, AR model of order. A -- double-precision real one-dimensional arrays, length (p 10). AR storage coefficient of a model (0), a (1 ),..., a (p). V -- double precision real-pointer, it forecast errors at power, AR model that inspired the white noise variance.
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压缩包 : 17869360burg.rar 列表 burg.doc burg.c