The nearest-neighbor method can successfully be applied to correct possible errors induced into bit strings transmitted over noisy communication channels or to classify samples into a prede ned set of categories. These two applications are investigated under real-time constraints, when the deadlines imposed can dramatically alter the quality of the solution unless a parallel model of computatio...

This paper presents a novel approach for accelerating the popular Reciprocal Nearest Neighbors (RNN) clustering algorithm, i.e. the fast-RNN. We speed up the nearest neighbor chains construction via a novel dynamic slicing strategy for the projection search paradigm. We detail an efficient implementation of the clustering algorithm along with a novel data structure, and present extensive experi...

A symbolic analysis of observed time series requires a discrete partition of a continuous state space containing the dynamics. A particular kind of partition, called "generating," preserves all deterministic dynamical information in the symbolic representation, but such partitions are not obvious beyond one dimension. Existing methods to find them require significant knowledge of the dynamical ...

We quantitatively analyze the performance of exact and approximate nearest-neighbors algorithms on increasingly high-dimensional problems in the context of sampling-based motion planning. We study the impact of the dimension, number of samples, distance metrics, and sampling schemes on the efficiency and accuracy of nearest-neighbors algorithms. Efficiency measures computation time and accuracy...

We report site percolation thresholds for square lattice with neighbor bonds at various increasing ranges. Using Monte Carlo techniques we found that nearest neighbors (NN), next-nearest neighbors (NNN), next-next-nearest neighbors (4N), and fifth-nearest neighbors (6N) yield the same pc = 0.592... . The fourth-nearest neighbors (5N) give pc = 0.298... . This equality is proved to be mathematic...

A climate system can be considered as a dynamical system with a chaotic behavior. This system is built onto different subsystems. One of them is the air temperature. This magnitude is of particular relevance on evapotranspiration models, general circulation models, and generally in any hydric budget model, becoming essential its determination as accurate as possible. Due to the fact that its va...

Cryptography facilitates selective communication through encryption of messages and or data. Block-cipher processing is one the prominent methods for modern cryptographic symmetric schemes. The rise in attacks on block-ciphers led to development more difficult However, attackers decrypt generic given sufficient time computing. Recent research had applied machine learning classification algorith...

In this work, we argue that current state-of-theart methods of aircraft localization such as multilateration are insufficient, in particular for modern crowdsourced air traffic networks with random, unplanned deployment geometry. We propose an alternative, a grid-based localization approach using the k-Nearest Neighbor (k-NN) algorithm, to deal with the identified shortcomings. Our proposal doe...

human action recognition is an important problem in computer vision. one of the methods that are recently used is sparse coding. conventional sparse coding algorithms learn dictionaries and codes in an unsupervised manner and neglect class information that is available in the training set. but in this paper for solving this problem, we use a discriminative sparse code based on multi-manifolds. ...