No abstract

The wavelet transform has become a powerful tool of signal analysis and is widely used in many applications which include signal detection and denoising. In hands free speech communication environments situation occurs that speech is superposed by background noise. Over the past few decades there is tremendous increase in the level of ambient environmental noise. This has been due to growth of technology. Noise is added by various factors like noisy engines, heavy machines, pumps, vehicles, over noisy telephone channel or using radio communication device in an aircraft cockpit. The wavelet denoising technique is called thresholding; it is a non linear algorithm. It can be decomposed in three steps. This paper is based on wavelet as denoising algorithm. Haar and Daubechies wavelets are implemented on speech signals and performance is evaluated.

No abstract

No abstract

This paper presents model based approach for diagnosis of open circuit power switch faults in full bridge DC-DC converter of a photovoltaic system. The control circuitry of the proposed converter monitors and regulates output current, whenever output current lowers, controller monitors current at test points and localizes faulty switch by comparing fault features. This minimizes efforts required for manual diagnosis of faulty switch. The faults will be detected and diagnosed automatically and displayed on LCD display. In this a model of DC-DC converter is prepared and simulated in SimPowerSystems toolset of MATLAB/Simulink and obtained results are presented.