-
theuseofmatlabinthetimeseries
介绍使用MATLAB软件对时间序列进行编程，里面有AR模型的建立方法(Describes the time series using MATLAB software programming, which has AR model method)
- 2010-06-04 16:50:40下载
- 积分：1
-
solvweight
Solves weighted absolute orientation problem using Horn s quaternion-based method
- 2010-10-11 06:59:04下载
- 积分：1
-
intface
fish语言建模，flac3的软件模型尺寸(fish language modeling, flac3 software model size)
- 2014-12-21 10:03:38下载
- 积分：1
-
com.yarin.android.FileManager.FileManager
Simple FileManager for Andorid
- 2015-04-13 11:20:32下载
- 积分：1
-
Calculation of intensities and peak pressure
超声换能器线性阵列声强和声压峰值计算案例(calculations of intensities and peak pressure of the linear arrays)
- 2018-01-31 21:40:07下载
- 积分：1
-
Edge-based-text-region-extraction-from-natural-im
The basic steps of the edge-based text extraction algorithm are given below
1. Create a Gaussian pyramid by convolving the input image with a Gaussian kernel
and successively down-sample each direction by half. (Levels: 4)
2. Create directional kernels to detect edges at 0, 45, 90 and 135 orientations.
3. Convolve each image in the Gaussian pyramid with each orientation filter.
4. Combine the results of step 3 to create the Feature Map.
5. Dilate the resultant image using a sufficiently large structuring element (7x7 [1])
to cluster candidate text regions together.
6. Create final output image with text in white pixels against a plain black
background.
- 2014-12-16 02:56:28下载
- 积分：1
-
bracket
bracket optimization method
- 2013-12-01 04:00:10下载
- 积分：1
-
BlindSignaSeparationalgorithm
speech processing for signal seperation
- 2010-09-06 02:42:13下载
- 积分：1
-
fastICA
基于负熵最大化的fastICA，matlab程序。程序中的公式在所附带的pdf文件中都高亮标明(Based on negative entropy maximization fastICA, matlab program. The formula in the program attached pdf file are highlighted marked)
- 2013-10-29 19:24:49下载
- 积分：1
-
lec5
Li near r egr essi on, acti ve learning
We arriv ed at the lo gistic regression model when trying to explicitly model the uncertainty
about the lab els in a linear c la ss ifier. The same genera l modeling approach p e rmits us to
use line ar predictio ns in var ious other co ntexts as well. The simplest of them is regress ion
where the go al is to pr e dict a con tin uous resp onse y
t ∈ R to e ach example ve ctor. Here
to o fo cusing on linear predictions won’t b e inherently limiting as linear predictions can b e
easily extended (ne xt lecture).
- 2013-12-02 14:38:57下载
- 积分：1
