Various areas like image processing, data compression and time frequency spectral estimation where the Wavelet have been applied. This paper describes another application in the filed of echocardiographic signals from an ultrasound machine. There are two areas of signals from the ultrasound echos-the imaging and the Doppler signals from blood flow in the chambers. Wavelet functions are shown to characterize Ultrasound data in terms of oriented texture component better. It can decorrelate noncoherent speckle noise better in the frequency domain. To determine the velocities of blood particles, the Doppler shift signals, synchronously detected with the base Ultrasound frequency, and called the I and Q signals are obtained. Rather than using the present day technique of CFFT method, the use of Wavelet decomposition of the signals has been made, using standard orthogonal Mallet Wavelet series, for example. Due to the usefulness of the Wavelets in providing better time resolution, particularly adjacent to the opening and closing instants of heart valves, the spectrogram based on Wavelet coefficients was found to be able to give improved resolution of the profiles of the E & A waves as well as in the evaluation of the pressure half-time for assessment of stenosed heart valve's area.
Infrasound is a low frequency acoustic phenomenon that typically ranges from 0.01 to 20 Hz. The data collected from infrasound microphones are presented online by the infrasound monitoring system operating in Northern Europe. Processing the continuous flow of data to extract optimal feature information is important for real-time signal classification. Performing wavelet decomposition on the real-time signals is an alternative. In this paper, we propose a novel, efficient VLSI architecture for the implementation of one-dimension, lifting-based discrete wavelet transform (DWT). Both of the folded and the pipelined schemes are applied in the proposed architecture; the former scheme supports higher hardware utilization and the latter scheme speed up the clock rate of the DWT. Our approach uses only two FIR filters, a high-pass and a low-pass filter. A compact implementation was realized with pipelining techniques and multiple uses of generalized building blocks. The design was described in VHDL and the FPGA implementation and simulation were performed on the Xilinx ISE
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