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This paper addresses the problem of adaptive modulation/demodulation scheme in the presence of interferences for wireless communication systems. We developed an adaptive modulation/demodulation scheme which modifies users' signature waveforms by maximizing the signal to interference ratio based on wavelet packet analysis and the state-of-art interference avoidance algorithms.
For the noise, blurry edge, bad contrast of the medical CT image, this article presents a medical CT image enhancing algorithm based on the mixture scope model of wavelet multi-scale transform. It uses wavelet multi-scale analysis to decompose the image signal to different direction sub-image, studies the different direction sub-pictorial information under the corresponding criterion by the different...
This article uses the advanced wavelet theory to perform multi-criteria transformation on the medical CT image wavelet in order to obtain directive components. The improved wavelet threshold value law is combined with the wavelet homomorphism filter corresponding to the obtained directive components to remove noise and enhance image effect, finally resulting in the multi-scale (level) enhanced images...
As the eco-environment source region of the Yellow River, Qinghai-Tibet plateau is the startup region of climate change in China and it's very sensitive to climate change. The streamflow in this study region decrease sharply since the mid- 1980s. The streamflow shows least cycle of 5-10 years by analyzing the streamflow data in 40 years of three gauging stations (Maduo, Jimai and Tangnaihai) based...
In this paper, we propose a ROI image watermarking algorithm for hiding secrete information in important image. The ROI information is segmented and extracted in original image, and then gray value supplement is made in that region to generate the disguised cover image, in which the ROI image encrypted by chaos is embedded based on lifting wavelet transform. Experiments show that the proposed watermarking...
For part I see ibid., p.Z001593-8 (2005). This work proposes and implements a novel classifier integrated with the wavelet transform and dynamic structural neural network for recognizing multiple power quality disturbances in a measured waveform. The classifier has been tested under different PQ events such as with single disturbance, dual disturbances and multiple disturbances. The experimental results...
This work develops a new approach to recognize multiple disturbances for a power quality (PQ) event in power systems. It is usual that several different types of disturbances simultaneously exist in a PQ event. However, most of the existing methods treat a PQ event as a single type of PQ disturbance. The performance of these methods might be limited and impracticable for application in the real power...
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