-
IDETutoriaxl
IDE接口的相当棒的资料 不看后悔 加油兄弟们 谢谢~(IDE interface rather stick information Bukanhouhui refueling brothers Thank you ~)
- 2010-01-28 23:22:10下载
- 积分：1
-
mainone
适合初学电力系统者，能够求出系统的雅克比矩阵，便于理解课本内容(Suitable for beginners power system, able to calculate the system Jacobian matrix, easy to understand textbook content)
- 2012-06-08 10:08:59下载
- 积分：1
-
lmd
局部均值分解源代码，难得的matlab程序代码(Local Mean Decomposition)
- 2011-09-29 15:09:24下载
- 积分：1
-
dzcl
海量工业数据处理使用，包括了稳态测试，剔除坏值，计算标准差和平均值等(Massive use of industrial data processing, including the steady-state test, remove bad values, calculate the standard deviation and mean, etc.)
- 2013-08-23 19:15:20下载
- 积分：1
-
subclustinializingfcm
subclutering initializing fcm:
开发语言：matlab
功能：使用减法聚类初始化fcm算法的聚类中心，可以快速找到合适的初始聚类中心(subclutering initializing fcm: the development of language: matlab function: the use of subtraction FCM clustering algorithm to initialize the cluster centers, can quickly find a suitable initial cluster centers)
- 2008-06-03 21:01:01下载
- 积分：1
-
prova
matlab script for speech recognition. in via of improvment
- 2011-10-22 19:22:42下载
- 积分：1
-
main-and-chil-mdi
MDI Parent Child- running procedure
- 2015-01-10 07:36:46下载
- 积分：1
-
Warshell2
无线传感器网络在不同节点数量下，连通率与通信半径的关系，利用蒙特卡洛方法仿真1000次(Relations between communications radiusand connectivity rate in WSN)
- 2014-07-01 09:19:58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
-
_AOSLevelsetSegmentationToolbox
这是一个matlab的源码。代码实现了图像的level set 分割方法(This is a matlab source. Code to achieve the level set image segmentation method)
- 2009-11-12 10:51:57下载
- 积分：1
