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By Subhransu Sekhar Dash, M. Arun Bhaskar, Bijaya Ketan Panigrahi, Swagatam Das
The booklet is a set of top of the range peer-reviewed study papers provided within the first overseas convention on foreign convention on synthetic Intelligence and Evolutionary Computations in Engineering structures (ICAIECES -2015) held at Velammal Engineering university (VEC), Chennai, India in the course of 22 – 23 April 2015. The ebook discusses big range of business, engineering and medical purposes of the rising innovations. Researchers from educational and current their unique paintings and trade rules, info, suggestions and purposes within the box of verbal exchange, Computing and gear Technologies.
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Extra resources for Artificial Intelligence and Evolutionary Computations in Engineering Systems: Proceedings of ICAIECES 2015
B) Obtaining the SNR. 99. ” If Ru(n) is less than or equal to U, the current speech frame can be considered as noise and then the algorithm will reestimate the noise variance. U ¼ ð1 À d Þ Â U þ d Â Ru ðnÞ ð13Þ A Fast Adaptive Kalman Filtering Algorithm for Speech … 15 (b) Obtaining the SNR When the noise is very large “(13),” the updating threshold cannot be used directly and hence the SNRs are calculated by determining the variance of pure speech signal, variance of input degraded speech signal, and variance of background noise.
Atallah et al. 6 repairs • The rated power of each turbine is (5 MW); the total installed power is (50 MW). • An offshore substation of (60 MVA) has a step-up transformer (150/36 kV). 9 million $/unit . • Cables characteristics used for power transmission are shown in Table 7. In the optimization case for simpliﬁcation: • Five wind speed scenarios will be taken into account. • Each system state might have at most one component unavailable. Input data: Mean wind speed at hub height 9 m/s. 152, Eq.
A fast adaptive Kalman ﬁltering algorithm for speech enhancement. In: IEEE International Conference on Automatic Science and Engineering Trieste, Italy, 2011. 8. Prabhavathi CN, Ravikumar KM. Acoustic noise classiﬁcation and characterisation using statistical properties. IJETAE, 2014;4 6:638. 9. Hua X. Adaptive speech enhancement based on discrete cosine transform in high noise environment. Harbin: Harbin Engineering University; 2006. Reliability Assessment and Economic Evaluation of Offshore Wind Farm Using Stochastic Probability Ahmed M.