Download Advances in Computer Science, Engineering & Applications by David C. Wyld (editor), Jan Zizka (editor), Dhinaharan PDF

By David C. Wyld (editor), Jan Zizka (editor), Dhinaharan Nagamalai (editor)

The foreign convention sequence on laptop technology, Engineering & functions (ICCSEA) goals to compile researchers and practitioners from academia and to target knowing laptop technological know-how, engineering and purposes and to set up new collaborations in those parts. the second one foreign convention on computing device technological know-how, Engineering & functions (ICCSEA-2012), held in Delhi, India, in the course of could 25-27, 2012 attracted many neighborhood and overseas delegates, featuring a balanced mix of mind and examine either from the East and from the West. Upon a strenuous peer-review strategy the easiest submissions have been chosen resulting in a thrilling, wealthy and a top quality technical convention software, which featured high-impact displays within the most up-to-date advancements of varied components of computing device technology, engineering and purposes examine.

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Extra resources for Advances in Computer Science, Engineering & Applications Proceedings of the Second International Conference on Computer Science, Engineering and Applications (ICCSEA 2012), May 25-27, 2012, New Delhi, India

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To increase signal to noise ratio various Pulse compression techniques were developed. Although there are analog pulse compressions techniques, digital pulse compression is more popularly used. C. Wyld et al. ): Advances in Computer Science, Eng. , AISC 166, pp. 13–23. com © Springer-Verlag Berlin Heidelberg 2012 14 B. Roja Reddy and M. Uttara Kumari codes. The performance criteria of a pulse compression sequence are judged by their autocorrelation properties [2]. The orthogonal waveforms used by the MIMO radar systems must be carefully designed to avoid the self-interference and detection confusion.

3 Generalized Gamma Mixture Model Today most of the research in speech processing is carried out by using Gaussian mixture model, but the main disadvantage with Gaussian mixture model is that it relies exclusively on the approximation and low in convergence, and also if Gaussian mixture model is used, the speech and the noise coefficients differ in magnitude [7]. To have a more accurate feature extraction, maximum posterior estimation models are to be considered [8]. Hence in this paper,a generalized gamma distribution is utilized for classifying the speech signal.

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