75 research outputs found
Active Noise Control using Variable step-size Griffiths’ LMS (VGLMS) algorithm on Real-Time platform
This paper proposes implementation of Griffith’s Variable step-size algorithm for Active Noise Control (ANC) on
ADSP-TS201 EZ-Kit Lite. The dual computational units and
execution of up to four instructions per cycle which are special features over other processors are best utilized to generate an optimized code. The VGLMS provides improved secondary path estimation and computations involved are marginal as the same gradient is used for step-size computation and coefficient adaptation. The improved secondary path estimate, in turn improves the ANC performance. Further, variable step-size algorithm is used for the main-path to achieve faster convergence. Both for narrowband (fundamental and its harmonics) and broadband noise fields, for a duct the attenuation achieved is 25 dB and 15 dB respectively. The program execution time was only 1.25% for an input sampling rate of 1 KHz which indicates the utility of the special features of the processor considered. Further these features have enabled in bringing down the program memory requirement in the implementation of the algorithm
Centroid Detection by Gaussian Pattern Matching in Adaptive Optics
Shack Hartmann wavefront sensor is a two dimensional array of lenslets which
is used to detect the incoming phase distorted wavefront through local tilt
measurements made by recording the spot pattern near the focal plane. Wavefront
reconstruction is performed in two stages - (a) image centroiding to calculate
local slopes, (b) formation of the wavefront shape from local slope
measurement. Centroiding accuracy contributes to most of the wavefront
reconstruction error in Shack Hartmann sensor based adaptive optics system with
readout and background noise. It becomes even more difficult in atmospheric
adaptive optics case, where scintillation effects may also occur. In this paper
we used a denoising technique based on thresholded Zernike reconstructor to
minimize the effects due to readout and background noise. At low signal to
noise ratio, this denoising technique can be improved further by taking the
advantage of the shape of the spot. Assuming a Gaussian pattern for individual
spots, it is shown that the centroiding accuracy can be improved in the
presence of strong scintillations and background.Comment: 6 pages, 14 figures, Accepted for publication in the International
Journal of Futuristic Computer Application
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