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EssentialMATLABforEngineersandScientists
Essential MATLAB for Engineers and Scientists
- 2010-02-24 00:39:24下载
- 积分：1
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p_music
说明： 现代数字信号处理中基于互相关函数的music方法(Modern digital signal processing in the cross-correlation function-based method of music)
- 2008-10-03 20:37:29下载
- 积分：1
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SRM
project on SRM drive system
The file is a Matlab m-file with all of the input parameters for the two Simulink models and It must be run prior to running the Simulink models to create the input parameters in the Matlab workspace. Because it is a Matlab m-file, it can be opened to change model input parameters. Once you have changed a parameter in you must run it again before you run the Simulink model to update the Matlab workspace and have the change take effect. The file is a Matlab m-file with all of the input parameters for the Simulink model.
- 2013-08-03 08:35:11下载
- 积分：1
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A10248044shuxuejianmo
研究生数学建模优秀论文，matlab，2012(2012 modeling paper)
- 2014-09-22 00:15:38下载
- 积分：1
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polyphase
这个是多相滤波的MATLAB程序，做接收机的同学可以参考的(this is a polyphase programme)
- 2013-11-06 20:01:53下载
- 积分：1
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DSP_pithshifter.m
這是一個讓原始音訊可以再不改變音訊長度下，改變pitch的程式，因為如果音訊用resample，雖然可改變其音訊頻率音高，但是卻會有拉長音訊的副作用，因此設計了一個可以改善其缺點的小方法(實做paper ）(This is an original audio so that you can no longer change the audio down the length of the program to change the pitch because if the audio with resample, although it can change the pitch of the audio frequency, but the audio will be stretched side effects, and thus can improve the design of a small way shortcomings (real do paper))
- 2014-01-07 23:05:03下载
- 积分：1
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thesis
这是一本关于多维图像处理的书籍，对这方面有研究的朋友可以参考一下，希望多多交流(This is a multi-dimensional image processing on the books, research in this area friends can make reference to the hope that more exchanges)
- 2008-01-17 11:11:07下载
- 积分：1
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DCDC
DC/DC converter的simulink模型(Simulink modell of DC/DC converter)
- 2018-01-12 16:37:53下载
- 积分：1
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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
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mud_code.tar
This code is for multiuser detection in communication
- 2009-06-05 20:02:54下载
- 积分：1
