The Cognitive Radio is the most emerging research area in communication and to bringing this technology into implementation the first and foremost challenge for researchers is the estimation of the spectral holes of a...
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ISBN:
(纸本)9781479980475
The Cognitive Radio is the most emerging research area in communication and to bringing this technology into implementation the first and foremost challenge for researchers is the estimation of the spectral holes of a wide band spectrum. So the spectral estimation techniques are most going to play a vital role in Cognitive Radio. In this paper we are proposing a novel non parametric spectral estimation technique for better spectral efficiency of the signal with minimized power errors in the estimation. erls Technique is introduced for better result of power signal spectral estimation. The erls Technique is the combination of wavelet algorithm and artificial neural network (ANN). The wavelet algorithm is used to extract the frequency components of the power signal. Then, using the neural network, the power error signals is determined. So, the complexity and computational time of spectral estimation are reduced.
In this correspondence, we establish a matrix pseudo-inversion lemma, and use it to develop an extended recursive least-squares (erls) algorithm. The erls algorithm is available for solving the over-determined normal ...
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In this correspondence, we establish a matrix pseudo-inversion lemma, and use it to develop an extended recursive least-squares (erls) algorithm. The erls algorithm is available for solving the over-determined normal equations in the instrumental variable approaches. The performance of the new algorithm is evaluated via computer simulations. (C) 2001 Elsevier Science B.V. All rights reserved.
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