-
neneifind
Find Nearest Neighbors on Sphere
- 2010-10-07 06:30:25下载
- 积分:1
-
NLmeansfilter
anisotropic diffusion
input: image to be filtered
t: radio of search window
f: radio of similarity window
k: degree of filtering
sigma: noise standard deviation
Author: Jose Vicente Manjon Herrera & Antoni Buades
Date: 09-03-2006
Implementation of the Non local filter proposed for A. Buades, B. Coll and J.M. Morel in
A non-local algorithm for image denoising
(anisotropic diffusion)
- 2015-01-11 14:32:33下载
- 积分:1
-
simran
bit error rate versus capacity
- 2013-11-28 09:40:04下载
- 积分:1
-
venkat
This is the paper for blood cell extraction in matlab.
- 2014-02-06 03:21:34下载
- 积分:1
-
LMS_Newton
用于仿真牛顿LMS算法(for LMS algorithm simulation Newton)
- 2005-01-18 13:28:56下载
- 积分:1
-
用matlab实现计算影像NDVI值的实例
用matlab实现计算影像NDVI值的实例,简单方便(NDVI images using matlab realize the value calculated instance, simple)
- 2021-04-28 16:58:44下载
- 积分:1
-
adaptive-filter-theory-4th
自适应滤波器原理第四版,经典中的经典,adaptive filter theory 4th(adaptive filter theory 4th)
- 2014-01-04 11:49:32下载
- 积分:1
-
1
matlab code for JTAG cable checking
- 2014-02-04 19:27:39下载
- 积分:1
-
SegyMAT
实现地震剖面图的数据读写,类似于SeiSee和Fimage的MATLAB程序包(similar to SeiSee and Fimage)
- 2018-05-09 14:20:16下载
- 积分:1
-
Iot-positioning-simulation
RSSI算法是指根据无线传感器接受到(目标物体)的信号指示强度,计算该信号在传播中的损耗,根据理论或者经验的信号传播模型将信号强度转换成距离。但是这种算法很容易受到天气,障碍物或人员流动的影响,导致测距不精确,从而定位精度不高。但是由于RSSI算法简单,成本低廉,很多无线通信模块提供RSSI值,所以RSSI算法依然应用在众多领域中。(RSSI algorithm is based on wireless sensor to receive the signal intensity (objects), calculate the signal in the transmission loss, according to the experience of the theory or the signal propagation model will be converted into a distance of signal strength.But this algorithm is very vulnerable to weather, obstacles or the influence of the flow of people, lead to range is not accurate, thus positioning accuracy is not high.But because the RSSI algorithm is simple, low cost, a lot of wireless communication module provides RSSI values, so the RSSI algorithm is used in many fields.)
- 2016-04-26 23:03:44下载
- 积分:1