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Nearest neighbor (NN) methods include at least six different groups of statistical methods. All have in common the idea that some aspect of the similarity between a point and its NN can be used to make useful inferences. In some cases, the similarity is the distance between the point and its NN; in others, the appropriate similarity is based on other identifying characteristics of the points. I...

Selection of neural network learning rates to obtain satisfactory performance from neural network controllers is a challenging problem. To assist in the selection of learning rates, this paper investigates robotic system sensitivity to neural network (NN) learning rate. The work reported here consists of experimental and simulation results. A neural network controller module, developed for the ...

We consider random multivariate quadtries obtained from n points independently and uniformly distributed on the unit cube of Rd. Let Nn(y) be the complexity of the standard partial match algorithm for fixed vector y, where y is a vector in Rs, 0 < s < d. We study Nn = supy Nn(y), the worst-case time for partial match. Among other things, we show that partial match is very stable, in the sense t...

INTRODUCTION Circulating nucleosomes released from apoptotic cells are important in the pathogenesis of systemic lupus erythematosus (SLE). Both nucleosomes and anti-nucleosome antibodies are deposited in inflamed tissues in patients with SLE. Active inflammation promotes nitration of tyrosine residues on serum proteins. Our hypothesis was that levels of nitrated nucleosomes would be elevated i...

Neural Networks (NN) have acquired great success, as they are one of the most rapidly expanding areas. Marketing and specifically Market Segmentation (MS) is one topic that NN can be a useful tool. This work presents an application of NN in MS. A Case Study (CS) in the market of mobile phones is used. In this scenario, a Mobile Company wants to predict what type of mobile phone people desire, i...