登录
首页 » C++ » envelope

envelope

于 2014-09-11 发布 文件大小:1KB
0 142
下载积分: 1 下载次数: 29

代码说明:

  在一个时间片下实现对信号的包络线提取,已测试(To achieve the extraction of the envelope signal at the next time slice, tested)

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • autoregression
    Input-Output Time-Series Prediction, Forecasting, Dyanamic modelling Nonlinear autoregression, System identification and Filtering
    2013-12-13 05:43:03下载
    积分:1
  • WNS101
    部分MATLAB仿真,优化覆盖,完成了一些,希望对大家有帮助(Part of the MATLAB simulation, optimization of coverage, completed some, we want to help)
    2011-05-26 10:05:02下载
    积分:1
  • APF
    APF的matlab实现,用matlab仿真有源电力滤波器,程序可以直接运行,可以看到补偿后的完美波形。(APF use matlab simulation)
    2015-05-01 09:48:42下载
    积分:1
  • qpsk
    ber of qpsk modulation
    2013-03-20 23:12:06下载
    积分:1
  • MATLAB
    Varios programas matlab
    2013-11-27 03:49:51下载
    积分:1
  • sayisal_2012yazfinal
    this program is matlab
    2013-04-17 03:55:42下载
    积分:1
  • Rapid.BeagleBoard.Prototyping.with.MATLAB.and
    belajar audio matlab asajaa
    2015-01-11 15:05:50下载
    积分:1
  • Gabor
    Gabor filter has implemented here to find the texture boundary by varying frequency and orientation angle.
    2015-02-20 20:12:42下载
    积分:1
  • dsa
    MATLAB CODE OF DIFFERENTIAL SEARCH ALGORITHM
    2012-11-01 17:17:19下载
    积分:1
  • gpml-matlab-v1.3-2006-09-08
    说明:  高斯过程(GP)模型中推理和预测的实现。它实现了在《Rasmussen & Williams:机器学习的高斯过程》(麻省理工学院出版社,2006)和《Nickisch & Rasmussen:二进制高斯过程分类的近似》(JMLR, 2008)中讨论的算法。该函数的优点在于灵活性、简单性和可扩展性。该函数具有一定的灵活性,首先通过定义均值函数和协方差函数来确定遗传算法的性质。其次,它允许指定不同的推理过程,如精确推理和期望传播(EP)。第三,它允许指定似然函数,如高斯函数或拉普拉斯函数(用于回归)和累积逻辑函数(用于分类)。简单性是通过一个简单的函数和紧凑的代码实现的。可扩展性是通过模块化设计来保证的,允许为已经相当广泛的推理方法、均值函数、协方差函数和似然函数库轻松添加扩展。(Gaussian Processes for Machine Learning , the MIT press, 2006 and Nickisch & Rasmussen: Approximations for Binary Gaussian Process Classification , JMLR, 2008. The strength of the function lies in its flexibility, simplicity and extensibility. The function is flexible as firstly it allows specification of the properties of the GP through definition of mean function and covariance functions. Secondly, it allows specification of different inference procedures, such as e.g. exact inference and Expectation Propagation (EP). Thirdly it allows specification of likelihood functions e.g. Gaussian or Laplace (for regression) and e.g. cumulative Logistic (for classification). Simplicity is achieved through a single function and compact code.)
    2020-02-26 20:39:48下载
    积分:1
  • 696518资源总数
  • 105540会员总数
  • 37今日下载