Aiming at the channel damage problems of multi-core fiber (Multi-core Fiber, MCF), AKNN (Adapted K-Nearest Neighbor) algorithm is proposed. The MATLAB software was used to simulate seven-core fiber, both inter-core crosstalk (Crosstalk, XT) and nonlinear effects were considered. Then KNN adapted equalize damaged signal receiver. simulation results show that possesses better BER performance lowe...

This paper analyzes k nearest neighbor classification with training data anonymized using anatomy. Anatomy preserves all data values, but introduces uncertainty in the mapping between identifying and sensitive values. We first study the theoretical effect of the anatomized training data on the k nearest neighbor error rate bounds, nearest neighbor convergence rate, and Bayesian error. We then v...

In solving pattern recognition problem in the Euclidean space, prototypes representing classes are de ned. On the other hand in the metric space, Nearest Neighbor method and K-Nearest Neighbor method are frequently used without de ning any prototypes. In this paper, we propose a new pattern recognition method for the metric space that can use prototypes which are the centroid of any three patte...

As a step towards neural realization of various similarity based algorithms k-NN method has been extended to weighted nearest neighbor scheme. Experiments show that for some datasets significant improvements are obtained. As an alternative to the minimization procedures a best–first search weighted nearest neighbor scheme has been implemented. A feature selection method for k-NN, based on a var...

Abstract In this paper we present an indexing method for probably approximately correct nearest neighbor queries in high dimensional spaces capable of improving the performance any index whose degrades with increased dimensionality query space. The basic idea is quite simple: use SVD to concentrate variance inter-element distance a lower space, Ξ. We do space and then “peek” forward from by gat...