-
Analyze
this code for analyse data and draw plot in matlab.
- 2014-08-18 15:03:17下载
- 积分：1
-
SeisLab_10.0301
约170勘探地震资料和测井资料的分析和显示功能（加上他们所谓的支持功能）的设置。这些功能读取和写入标准的SEG - Y格式的地震数据，读取和写入测井在LAS格式2.0（也读3.0 LAS格式），并执行许多通常对这些数据类型进行的操作。他们使用标准化的结构来表示地震数据和测井数据，从而使函数调用的简单串联。(A set of about 170 functions (plus support functions called by them) for analysis and display of exploration-seismic data and well logs. These functions read and write seismic data in standard SEG-Y format, read and write well logs in LAS-format 2.0 (also read LAS-format 3.0), and perform many of the manipulations usually performed on these data types. They use standardized structures to represent seismic data and well data and thus allow simple concatenation of function calls.)
- 2011-09-28 16:59:00下载
- 积分：1
-
main_beta_1021
imu和视觉里程计 kalman滤波器 进行融合(imu VO fusion)
- 2020-07-02 08:00:02下载
- 积分：1
-
noise
加高斯噪声，椒盐噪声，复杂高斯噪声，复杂传统噪声(salt&pepper noise ；gaussian noise ；multiplicative gaussian；multiplicative uniform)
- 2011-01-15 21:44:17下载
- 积分：1
-
clockscotts
This code will display a scotts clock. this code is done in MATLAB.
- 2015-02-06 01:26:04下载
- 积分：1
-
lovsub_page
Implementation of cl_page for LOVSUB layer.
- 2014-09-17 21:22:15下载
- 积分：1
-
bayesgauss
Bayesian gauss algorithm
- 2013-04-29 16:58:28下载
- 积分：1
-
Matlab-Training-Basic
matlab在金融方面应用的内部培训，基础篇(internal training matlab applications in finance, Basics)
- 2014-05-20 18:57:33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
-
mga
经典的多目标程序，可以生成界面的，希望大家喜欢。(Classical multi-objective procedure, the interface can be generated, and I hope everyone likes.)
- 2007-09-26 21:49:14下载
- 积分：1
