The classical k nearest neighbor (k-nn) classification assumes that a fixed global metric is defined and searching for nearest neighbors is always based on this global metric. In the paper we present a model with local induction of a metric. Any test object induces a local metric from the neighborhood of this object and selects k nearest neighbors according to this locally induced metric. To in...

This work deals with the influence of neighborhood in simple rock–paper–scissors models biodiversity. We consider case three distinct species which evolve under standard rules mobility, reproduction and competition. The rule competition follows guidance game, prey being annihilated, leaving an empty site accordance May-Leonard proposal for predator use von Neumann neighborhood, but we mobility ...

due to the algorithmic simplicity, cellular automata (ca) models are useful and simple methods in structural optimization. in this paper, a cellular-automaton-based algorithm is presented for simultaneous shape and topology optimization of continuum structures, using five-step optimization procedure. two objective functions are considered and the optimization process is converted to the single ...

Abstract In this article, we introduce the notion of complementary soft neighborhood and present three kinds covering rough set ( $$\mathcal {CSR}$$ CSR ) models. The basic properties these models are investigated. relationships among also discussed. Moreover, establish topological approach to say, $$\varDelt...

Unlike traditional classification tasks, multilabel classification allows a sample to associate with more than one label. This generalization naturally arises the difficulty in classification. Similar to the single label classification task, neighborhood-based algorithms relying on the nearest neighbor have attracted lots of attention and some of them show positive results. In this paper, we pr...

The natural duality between “topological” and “regular,” both considered as convergence space properties, extends naturally top-regular convergence spaces, resulting in the new concept of a p-topological convergence space. Taking advantage of this duality, the behavior ofp-topological andp-regular convergence spaces is explored, with particular emphasis on the former, since they have not been p...

This work introduces Mutual Proximity, an unsupervised method which transforms arbitrary distances to similarities computed from the shared neighborhood of two data points. This reinterpretation aims to correct inconsistencies in the original distance space, like the hub phenomenon. Hubs are objects which appear unwontedly often as nearest neighbors in predominantly high-dimensional spaces. We ...

Electromyographic (EMG) signal provide a significant source of information for diagnosis, treatment and management of neuromuscular disorders.Neuromuscular diseases changes, the shape and characteristics of the motor unit action potentials (MUAPs). The MUAPs detected from myopathic patients are characterized by high frequency contents, low peak-to-peak amplitude and MUAPs neuropathic patients a...