In this papel; we present an approximate nearest neighbor search algorithm that use heuristics to decide whether o r not to access a node in the index tree based on three interesting data distribution properties. We demonstrate that the proposed algorithm significantly reduces the number of nodes accessed over the algorithms that have been proposed in earlier works. Also, it will be demonstrate...

A brain computer interface BCI enables direct communication between a brain and a computer translating brain activity into computer commands using preprocessing, feature extraction, and classification operations. Feature extraction is crucial, as it has a substantial effect on the classification accuracy and speed. While fractal dimension has been successfully used in various domains to charact...

We propose an image interpolation algorithm that is nonparametric and learning-based, primarily using an adaptive k-nearest neighbor algorithm with global considerations through Markov random fields. The empirical nature of the proposed algorithm ensures image results that are data-driven and, hence, reflect "real-world" images well, given enough training data. The proposed algorithm operates o...

Nearest neighbor search and k-nearest neighbor graph construction are two fundamental issues arise from many disciplines such as information retrieval, data-mining, machine learning and computer vision. Despite continuous efforts have been taken in the last several decades, these two issues remain challenging. They become more and more imminent given the big data emerges in various fields and h...

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...