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muisui

于 2016-04-20 发布 文件大小:7KB
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  可以实现模式识别领域的数据的分类及回归,利用自然梯度算法,是机器学习的例程。( You can achieve data classification and regression pattern recognition, Use of natural gradient algorithm, Machine learning routines.)

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  • hht.new
    能够把输入信号分解为多个IMF分量,并进行Hilbert变换,求得信号的时频分布谱图。(Be able to input signal is decomposed into several IMF components and carry out Hilbert transform, time-frequency distribution obtained spectrum.)
    2009-12-03 09:48:57下载
    积分:1
  • wendingxing
    不怕明确地告诉你,这个东西啊,可以很放方便地判别运动状态的稳定性(Stability Criteria)
    2014-11-03 19:18:01下载
    积分:1
  • SINS_DVL
    惯导和多普勒组合滤波器设计的详细程序,其中使用的是卡尔曼滤波技术。(the program of the integrated navigation about SINS and DVL)
    2021-01-04 14:18:56下载
    积分:1
  • omp-and-JS-OMP
    压缩感知的解压缩OMP算法。有详细的注释(The compressed sensing decompression OMP algorithm. Detailed notes)
    2013-04-28 22:09:30下载
    积分:1
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    simple simulink model of FSK
    2010-10-21 13:54:08下载
    积分:1
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    文件为通信系统中散粒噪声以及高斯有色噪声matlab建模(File Modeling for Particle Noise and Gauss Colored Noise in Communication System by MATLAB)
    2020-10-30 12:29:56下载
    积分:1
  • 73462684DQPSK_Sim
    match filter simulation program
    2009-05-09 02:41:11下载
    积分:1
  • judger
    最小错误率和最小风险贝叶斯分类器,附带示例数据(Minimum error rate and minimum risk Bayes classifier, with sample data)
    2010-03-12 10:45:24下载
    积分:1
  • pid
    以中等纯度的精馏塔为研究对象,考虑到不等分子溢流的影响和非理想的汽液平衡,可以得到塔顶产品轻组分含量Y与回流量L之间的传递函数为: 其中由于现场环境干扰,输出带有测量噪声是(0,1)的正态分布序列,它的方差为ɑ=0.5。由于输出中带有很大的噪声信号,故将数字滤波技术中常见的低通滤波器由于偏差控制,滤掉其中的噪声信号,然后在对其进行PID计算,得到实际的控制量。在该方法在噪声较强的环境下,可以得到较好的控制效果。 控制要求: 1、 采用带低通滤波器的增量式PID将塔顶轻组分含量控制在0.99 2、 用ISTE法整定PID参数 3、 在控制过程中,到150周期加入幅度为-20 的阶跃干扰,在第300周期干扰消失。分析PID参数的抗干扰性。 (Medium-purity distillation column, taking into account ranging from molecular overflow and non-ideal vapor-liquid equilibrium, the transfer function between the light component content of the top product Y and the back flow L can be obtained as: Because the field of environmental interference, output with the measurement noise is a normal distribution (0,1) sequence, its variance ɑ = 0.5. As with a lot of noise in the output signal, it will be common in low-pass filter in the digital filtering techniques due to the bias control, filter out the noise signal, then its PID, the actual amount of control. In the strong noise environment, you can get better control effect. Control requirements: 1, using the incremental PID with a low-pass filter to the top of the tower content of light components in the 0.99 2, the method of ISTE tuning PID parameters 3, in the control process, to 150 cycles join the range of-20 step disturbance, disappearance of interference in the first 300 c)
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