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BruteSearch

  • Category : matlab
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  • Update : 2012-11-26
  • Size : 4kb
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  • Author :M*****
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Introduction - If you have any usage issues, please Google them yourself
The following utilities are provided: - Nearest neighbor - K-Nearest neighbors - Radius Search They al supports N-dimensions and work on double, it is possible to choose if return the distances. Here is a time comparison with a vectrized m-code: N=1000000 number of reference points Nq=100 number of query points dim=3 dimension of points k=3 number of neighbor tic [idc,dist]=BruteSearchMex(p ,qp , k ,k) MEX toc tic [idc,dist]=knnsearch(qp,p,k) VECTORIZED M-CODE toc p=rand(N,dim) qp=rand(Nq,dim) Output: Elapsed time is 0.962640 seconds. Elapsed time is 18.813100 seconds.
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BruteSearchMex.cpp
BruteSearchTranspose.cpp
TestBruteSearch.m
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