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 CURRENT ISSUES
 Volume 1, Issue 2, Feb 2013
 
 

Volume 1, Issue 2, February 2013


International Journal of Advance Research in Mathematics and Mathematical Sciences (IJOARM)
 
 

Fractal: A set which is larger than the universe[ ]


Fractal is a set, which geometric pattern is self-similar at different scales. It has a fractal dimension, which strictly exceeds its topological dimension. It can be a non-integer. We calculate fractal dimension for only exact self-similar fractals. We show a strong link between chaos theory and fractals in an informal manner and study about space-filling curves, which are special type of fractals having fractal dimension two. Fractals need not only to be self- similar in nature. We explain about different types of fractals depending upon their geometric patterns. Finally we discuss about the Mandelbrot set, one of the most complex structure in mathematics and the Julia set. The Julia set can be connected or disconnected. The connectedness of the Julia set depends on the structure of the Mandelbrot set.

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Extracta Mathematicae: A Scientometric Analysis[ ]


Scientometric analysis of 77 articles published in the extracta mathematicae during the year 2007 to 2010 are taken up to abserve the distribution of contributions ( volume – wise ), authorship pattern of contributions ( volume – wise ), contributions ( institutions – wise ), types of publications cited, average citation per contribution in each volume, subjectwise distribution of articles. Results indicate that highest number of papers have been written by single authors. The growth and popurality of this journal is found to show an ( increase ) upward trend.

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Analysis Of Backpropagation Algorithm[ ]


In this paper we will discuss the analysis of back propagation algorithm by implementation of this algorithm in metlab. And after implementation try to determine why or why not this algorithm is used in feed forward and feed backward multilayer neural network.

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Correlation Analysis: The Bootstrap Approach[ ]


For a general class of problems, the bootstrap method of resampling is one of the possible methods of constructing tests of significance. The sampling distribution of a test statistic for an experiment compiled by the bootstrap approach requires no reference to the population distribution and therefore no requirement that it should conform to a mathematically definable frequency distribution. Algorithms for the bootstrap distribution of correlation coefficients are presented and implemented. As an illustrative example, a critical value for Pearson’s product moment correlation coefficients and Spearman’s rank correlation coefficients are produced for a given set of data.

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