登录
首页 » matlab » entropy

entropy

于 2009-02-14 发布 文件大小:1KB
0 265
下载积分: 1 下载次数: 5

代码说明:

  entropy of ofdm inter carrier interference scheme

文件列表:

entropy.m

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

  • matllab_tips
    First keep in mind that this is not a Matlab tutorial. This is just a list of tricks I have found useful while writing the toolboxes available on the Matlab Central repository.
    2009-11-01 04:34:45下载
    积分:1
  • Minic-S.
    DIGITAL STEGANOGRAPHY TECHNOLOGY
    2014-11-21 12:00:41下载
    积分:1
  • SPP
    GPS单点定位程序,包括广播星历读取,计算卫星位置等功能。(GPS single point positioning procedures, including The broadcast ephemeris reading, calculate the satellite position.)
    2021-04-24 22:48:46下载
    积分:1
  • melcode
    Convex Optimization, network model
    2011-12-09 03:27:14下载
    积分:1
  • LMI2
    LMI2 For control systems
    2014-11-08 11:44:32下载
    积分:1
  • stability_modeling_of_motor
    In any power system, stability is always a important parameter. To check the stability of a synchronous generator which is connected with the grid is the power angle and freq need to know. With the help of this simulation model one can easily find Power angle and Freq.
    2015-11-13 13:38:45下载
    积分:1
  • yanzhengpinyuweifenhejifen
    验证运用频域方法进行微分和积分准确性的程序(this is a program about validating caculous)
    2009-06-01 21:52:35下载
    积分:1
  • ccysz
    本文档内的源码 内容为图像分割技术在matlab中的代码 适合初学者和matlab爱好者(The source of the content within this document image segmentation code in MATLAB for beginners and Matlab lovers)
    2013-05-21 18:55:27下载
    积分:1
  • 1807.01622
    说明:  深度神经网络在函数近似中表现优越,然而需要从头开始训练。另一方面,贝叶斯方法,像高斯过程(GPs),可以利用利用先验知识在测试阶段进行快速推理。然而,高斯过程的计算量很大,也很难设计出合适的先验。本篇论文中我们提出了一种神经模型,条件神经过程(CNPs),可以结合这两者的优点。CNPs受灵活的随机过程的启发,比如GPs,但是结构是神经网络,并且通过梯度下降训练。CNPs通过很少的数据训练后就可以进行准确的预测,然后扩展到复杂函数和大数据集。我们证明了这个方法在一些典型的机器学习任务上面的的表现和功能,比如回归,分类和图像补全(Deep neural networks perform well in function approximation, but they need to be trained from scratch. On the other hand, Bayesian methods, such as Gauss Process (GPs), can make use of prior knowledge to conduct rapid reasoning in the testing stage. However, the calculation of Gauss process is very heavy, and it is difficult to design a suitable priori. In this paper, we propose a neural model, conditional neural processes (CNPs), which can combine the advantages of both. CNPs are inspired by flexible stochastic processes, such as GPs, but are structured as neural networks and trained by gradient descent. CNPs can predict accurately with very little data training, and then extend to complex functions and large data sets. We demonstrate the performance and functions of this method on some typical machine learning tasks, such as regression, classification and image completion.)
    2020-06-23 22:20:02下载
    积分:1
  • cinertia
    移动机器人的matlab仿真程序,很好用的,值得学习(Mobile robot matlab simulation program, the good, it is worth learning)
    2013-09-01 17:01:42下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载