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KNN-complexity-reduced-method
基于LANDMARC的定位系统上进行的算法复杂度的减小的优化,包括了具体的优化后系统的实现,误差前后对比,改文章还提出了一种adaptive的定位算法,更利于外部变化环境下(In wireless networks, a client’s locations can be estimated using signal strength received from signal transmitters. Static
fingerprint-based techniques are commonly used for location estimation, in which a radio map is built by calibrating signal-strength
values in the offline phase. These values, compiled into deterministic or probabilistic models, are used for online localization. However,
the radio map can be outdated when signal-strength values change over time due to environmental dynamics, and repeated data
calibration is infeasible or expensive. In this paper, we present a novel algorithm, known as Location Estimation using Model Trees
(LEMT), to reconstruct a radio map by using real-time signal-strength readings received at the reference points. This algorithm can
take real-time signal-strength values at each time point into account and make use of the dependency between the estimated locations
and reference points. We show that this technique can effectively accommodat)
- 2011-02-11 22:16:05下载
- 积分:1
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axescenter
matlab graphic file , axis
- 2013-01-08 06:48:22下载
- 积分:1
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2004
matlab coding for dip
- 2012-11-19 03:16:52下载
- 积分:1
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anp
NP是美国匹兹堡大学的T.L.Saaty 教授于1996年提出了一种适应非独立的递阶层次结构的决策方法,它是在网络分析法(AHP)基础上发展而形成的一种新的实用决策方法。其关键步骤有以下几个:
1 确定因素,并建立网络层和控制层模型。
2 创建比较矩阵。
3 按照指标类型针对每列进行规范化。
4 求出每个比较矩阵的最大特征值和对应的特征向量。
5 一致性检验。如果不满足,则调整相应的比较矩阵中的元素。
6 将各个特征向量单位化(归一化),组成判断矩阵。
7 将控制层的判断矩阵和网络层的判断矩阵相乘,得到加权超矩阵。
8 将加权超矩阵单位化(归一化),求其K次幂收敛时的矩阵。其中第j列就是网络层中各元素对于元素j的极限排序向量。
(NP is a professor at the University of Pittsburgh TLSaaty presented in 1996, an adaptation of non-independent Hierarchy of decision-making method, which is the analytic network process (AHP) formed on the basis of the development of a new and practical decision-making method . The key steps are the following:
A determining factor, and a network layer and control layer model.
2 create a comparison matrix.
For each of the three types of indicators in accordance with normalized columns.
4 find the maximum for each comparison matrix eigenvalue and the corresponding eigenvectors.
5 consistency test. If not satisfied, then the comparison to adjust the corresponding matrix elements.
6 will each feature vector units of (normalized), to determine the composition of matrix.
7 to determine the control layer and network layer to determine matrix matrix multiplication, to be weighted super-matrix.
8 of the weighted super-matrix units of (normalized), seeking the powe)
- 2010-01-28 09:36:45下载
- 积分:1
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zf2wc
Calculation wc and kd on a desirable stock of stability of a contour
- 2010-02-17 21:22:02下载
- 积分:1
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05978173
Phase-Based UHF RFID Tracking With Nonlinear
Kalman Filtering and Smoothing
- 2014-10-13 02:33:35下载
- 积分:1
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CHW1
mean and covariance of samples estimation
- 2014-12-23 01:41:35下载
- 积分:1
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RobustPAST_Tracking
PAST算法,利用PAST算法实现信号来波方向角估计。文件还为MUSIC, ESPRIT算法一起进行了仿真比较。(PAST algorithm, using PAST algorithm for signal DOA angle estimation. The document also is MUSIC, ESPRIT algorithms were simulated and compared together.)
- 2021-04-01 10:19:08下载
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publidownload.fr
MIMO ofdm in matlab analysys
- 2009-05-07 10:27:50下载
- 积分:1
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a
说明: this m.file is about wsn
- 2011-05-05 15:12:57下载
- 积分:1