Deep neural networks with several layers have during the last years become a highly successful and popular research topic in machine learning due to their excellent performance in many benchmark problems and applications. A key idea in deep learning is to not only learn the nonlinear mapping between the inputs and outputs, but also the underlying structure of the data (input) vectors. In this c...

The evolutionary adaptations of functional genes to life at high pressure are not well understood. To elucidate the mechanisms of protein adaptation to high pressure, we cloned the myosin heavy chain (MyHC) cDNA from skeletal muscle of two deep-sea fishes, Coryphaenoides yaquinae and C. armatus, and two non-deep-sea fishes, C. acrolepis and C. cinereus. The MyHCs of deep-sea fishes have a uniqu...

turkish words in the texts of persian language and literature show the deep and long relations between two languages. and because the diwan-e-hafiz (hafiz’s complete works), in which the persian lyric poetry achieves its most flourishing perfection, is not an exception, some of its 35 turkish words are going to be surveyed to determine their morphophonemic in this paper. hoping to be considered...

Deep networks can potentially express a learning problem more efficiently than local learning machines. While deep networks outperform local learning machines on some problems, it is still unclear how their nice representation emerges from their complex structure. We present an analysis based on Gaussian kernels that measures how the representation of the learning problem evolves layer after la...

Over the past few years, deep learning has risen to foreground as a topic of massive interest, mainly result successes obtained in solving large-scale image processing tasks. There are multiple challenging mathematical problems involved applying learning: most methods require solution hard optimisation problems, and good understanding trade-off between computational effort, amount data model co...