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soft Demapping QPSK : LLR computation using Euclidian distance approach, Parallel-to-Serial converter : needs I and Q components of QPSK symbols at the input,soft Demapping QPSK : LLR computation using Euclidian distance approach, Parallel-to-Serial
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模拟退火和对称
*欧几里德旅行商问题。
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*为基础的解决办法的本地搜索启发式
*非过境道路和近邻
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* Simulated annealing and the Symetric
* Euclidian Traveling Salesman Problem.
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* Solution based on local search heuristics for
* non-crossing paths and nearest neighbor
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good version of soft Demapping QPSK : LLR computation using Euclidian distance approache, Parallel-to-Serial converter, needs I and Q componets of QPSK symbols at the input
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soft Demapping 8PSK : LLR computation using Euclidian distance approach, Parallel-to-Serial converter, needs I and Q componets of 8PSK symbols at the input
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corrected version of Demapping QPSK : LLR computation using Euclidian distance approach, Parallel-to-Serial converter, needs I and Q componets of QPSK symbols at the input
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Demapping 8PSK : LLR computation using Euclidian distance approach, Parallel-to-Serial converter, Hard decision, needs I and Q componets of 8PSK symbols at the input
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Euclidean Distance Transform has been widely studied in computational geometry, image processing, computer graphics and pattern recognition. Euclidean distance has been computed through different algorithms like parallel, linear time algorithms etc.
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Focused on the disadvantage of classical Euclidian
distance in data clustering analysis, we propose an improved
distance calculation formula, which describes the local
compactness and global connectivity between data points.
Furthermore, we i
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it is a collection of matlab program.
1.to find the euclidian distance
2.to create mel frequency filter bank
3.
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After identifying the best MNT− 1 nodes with the simplified branch metric and the accumulated branch metric at stage NT − 1, we then calculate the LLR of each coded bit utilizing the standard squared Euclidian distance metric.
The log-lik
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Theme: Object recognition using Geometric Properties(area, perimeter,circularity,etc) . In order to obtain the results the project was implemented using C++ and the tool C++Builder. For every geometric feature has been created a method that return a
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this code calculate the euclidian distance.
h = waitbar(0, Distance Computation )
switch nargin
case 1-this code calculate the euclidian distance.
h = waitbar(0, Distance Computation )
switch nargin
case 1
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Returns the square of the Euclidian distance to (dx,dy).
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