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Proceedings of

International Conference on Advances in Electronics and Communication Engineering ECE 2012

Date
14-Jul-2012
Location
singapore , United Kingdom
Authors
4
ISBN
978-981-07-2969-1

2 Articles Published

1. ANALYSIS OF PSEUDO-NMOS LOGIC WITH REDUCED STATIC POWER IN DEEP SUB-MICRON REGIME

Authors: M. JANAKI RANI , S. MALARKKAN

Abstract: The growing demand for high density VLSI circuits result in scaling of supply voltage and an exponential increase of leakage or static power in deep sub-micron technology. Therefore reducing static power consumption of portable devices such as cell phones and laptop computers is highly desirable for a longer battery life. In this paper we propose two power reduction techniques such as reverse body bias and transistor stacking for reducing the static power of Pseudo NMOS logic circuits that have very high static power consumption. The simulation results show that the static power decreases with both the methods and the combined effect of reverse body bias and stack method gives the least static current. The simulations are done at 65nm and 45nm process technologies using HSPICE at a temperature of 27C with two different supply voltages of 1v and 0.3v.

Keywords: Pseudo-NMOS logic, process technology, reverse body bias, transistor stack, static power.

Pages: 1 - 4 | DOI: 10.15224/978-981-07-2969-1-123

2. ALGORITHM FOR DENOISING OF UNDERWATER ACOUSTIC SIGNAL USING ENSEMBLE EMPIRICAL MODE DECOMPOSITION

Authors: V.RAJENDRAN2, , V.VIJAYABASKAR

Abstract: The main focus of this paper is denoising of underwater acoustic signal to improve the performance of underwater acoustic instruments. The major sources of underwater ambient noises are distant shipping, wind, rain and biological activities. In this paper we have considered wind driven noise, which occupies wide bandwidth,as ambient noise source. A lot of research work has been done on denoising and most of the researchers have used wavelet as the denoising tool. In this paper we have proposed a novel denoising algorithm based on EEMD (Ensemble Empirical Mode Decomposition) , which is mainly suitable for non-linear and non-stationary signals. The results presented here will give an insight on the performance of this adaptive algorithm.

Keywords: Feature Extraction, Arabic Character Recognition, Feature Fusion.

Pages: 5 - 11 | DOI: 10.15224/978-981-07-2969-1-160

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