A two-dimensional genetic algorithm of wavelet coefficient is presented by using the ENO wavelet transform and the decomposed characterization of the two-dimensional Haar wavelet. And simulated by the ENO interpolatio...A two-dimensional genetic algorithm of wavelet coefficient is presented by using the ENO wavelet transform and the decomposed characterization of the two-dimensional Haar wavelet. And simulated by the ENO interpolation the article shows the affectivity and the superiority of this algorithm.展开更多
An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square er...An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.展开更多
This paper presents an analysis on and experimental comparison of several typical fast algorithms for discrete wavelet transform (DWT) and their implementation in image compression, particularly the Mallat algorithm, ...This paper presents an analysis on and experimental comparison of several typical fast algorithms for discrete wavelet transform (DWT) and their implementation in image compression, particularly the Mallat algorithm, FFT-based algorithm, Short- length based algorithm and Lifting algorithm. The principles, structures and computational complexity of these algorithms are explored in details respectively. The results of the experiments for comparison are consistent to those simulated by MATLAB. It is found that there are limitations in the implementation of DWT. Some algorithms are workable only for special wavelet transform, lacking in generality. Above all, the speed of wavelet transform, as the governing element to the speed of image processing, is in fact the retarding factor for real-time image processing.展开更多
In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung so...In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung sounds(sounds with wheezes or rales). The proposed method includes two main steps: Firstly, the wavelet packet transform(WPT) is used to extract the original features of lung sounds; then the genetic algorithm(GA) is used to select the best feature set. The obtained optimal feature set is sent to four different classifiers to evaluate the performance of the proposed method. Experimental results show that the feature set obtained by the proposed method provides a higher classification accuracy of 94.6% in comparison with the best wavelet packet basis approach and multi-scale principal component analysis(PCA) approach. Meanwhile, the proposed method has effective generalization performance and can obtain the best feature set without priori knowledge of lung sounds.展开更多
A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark,...A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark, and then the embedding and extraction of watermark are implemented in digital wavelet transform (DWT) domain. During the watermarking process, GA is employed to search optimal parameters of embedding strength and times of Arnold transform to gain the optimization of watermarking performance. Simulation results show that the proposed method can improve the quality of watermarked image and give almost the same robustness of the watermark.展开更多
为保障医院信息网络的安全管理,避免医疗信息泄露,提出了基于深度生成模型的医院网络异常信息入侵检测算法。采用二进制小波变换方法,多尺度分解医院网络运行数据,结合自适应软门限去噪系数提取有效数据。运用最优运输理论中的Wasserst...为保障医院信息网络的安全管理,避免医疗信息泄露,提出了基于深度生成模型的医院网络异常信息入侵检测算法。采用二进制小波变换方法,多尺度分解医院网络运行数据,结合自适应软门限去噪系数提取有效数据。运用最优运输理论中的Wasserstein距离算法与MMD(Maximun Mean Discrepancy)距离算法,在深度生成模型中,对医院网络数据展开降维处理。向异常检测模型中输入降维后网络正常运行数据样本,并提取样本特征。利用深度学习策略中的Adam算法,生成异常信息判别函数,通过待测网络运行数据与正常网络运行数据的特征对比,实现医院网络异常信息入侵检测。实验结果表明,算法能实现对医院网络异常信息入侵的高效检测,精准检测多类型网络入侵行为,为医疗机构网络运行提供安全保障。展开更多
基金the National Natural Science Committee and Chinese Engineering Physics Institute Foundation(10576013)the National Nature Science Foundation of Henan Province of China(0611053200)+1 种基金the Natural Science Foundation for the Education Department of Henan Province of China(2006110001)the Nature Science Foundation of Henan Institute of Science and Technology(2006055)
文摘A two-dimensional genetic algorithm of wavelet coefficient is presented by using the ENO wavelet transform and the decomposed characterization of the two-dimensional Haar wavelet. And simulated by the ENO interpolation the article shows the affectivity and the superiority of this algorithm.
基金Sponsored by the Nature Science Foundation of Jiangsu(BK2009410)
文摘An orthogonal wavelet transform fractionally spaced blind equalization algorithm based on the optimization of genetic algorithm(WTFSE-GA) is proposed in viewof the lowconvergence rate,large steady-state mean square error and local convergence of traditional constant modulus blind equalization algorithm(CMA).The proposed algorithm can reduce the signal autocorrelation through the orthogonal wavelet transform of input signal of fractionally spaced blind equalizer,and decrease the possibility of CMA local convergence by using the global random search characteristics of genetic algorithm to optimize the equalizer weight vector.The proposed algorithm has the faster convergence rate and smaller mean square error compared with FSE and WT-FSE.The efficiency of the proposed algorithm is proved by computer simulation of underwater acoustic channels.
基金the Natural Science Foundation of China (No.60472037).
文摘This paper presents an analysis on and experimental comparison of several typical fast algorithms for discrete wavelet transform (DWT) and their implementation in image compression, particularly the Mallat algorithm, FFT-based algorithm, Short- length based algorithm and Lifting algorithm. The principles, structures and computational complexity of these algorithms are explored in details respectively. The results of the experiments for comparison are consistent to those simulated by MATLAB. It is found that there are limitations in the implementation of DWT. Some algorithms are workable only for special wavelet transform, lacking in generality. Above all, the speed of wavelet transform, as the governing element to the speed of image processing, is in fact the retarding factor for real-time image processing.
基金Funded by the International Science and Technology Cooperation Foundation of Chongqing Science and Technology Commission(Grant No.cstc2012gg-gjhz0023)the 2013 Innovative Team Construction Project of Chongqing Universities
文摘In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung sounds(sounds with wheezes or rales). The proposed method includes two main steps: Firstly, the wavelet packet transform(WPT) is used to extract the original features of lung sounds; then the genetic algorithm(GA) is used to select the best feature set. The obtained optimal feature set is sent to four different classifiers to evaluate the performance of the proposed method. Experimental results show that the feature set obtained by the proposed method provides a higher classification accuracy of 94.6% in comparison with the best wavelet packet basis approach and multi-scale principal component analysis(PCA) approach. Meanwhile, the proposed method has effective generalization performance and can obtain the best feature set without priori knowledge of lung sounds.
文摘A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark, and then the embedding and extraction of watermark are implemented in digital wavelet transform (DWT) domain. During the watermarking process, GA is employed to search optimal parameters of embedding strength and times of Arnold transform to gain the optimization of watermarking performance. Simulation results show that the proposed method can improve the quality of watermarked image and give almost the same robustness of the watermark.
文摘为保障医院信息网络的安全管理,避免医疗信息泄露,提出了基于深度生成模型的医院网络异常信息入侵检测算法。采用二进制小波变换方法,多尺度分解医院网络运行数据,结合自适应软门限去噪系数提取有效数据。运用最优运输理论中的Wasserstein距离算法与MMD(Maximun Mean Discrepancy)距离算法,在深度生成模型中,对医院网络数据展开降维处理。向异常检测模型中输入降维后网络正常运行数据样本,并提取样本特征。利用深度学习策略中的Adam算法,生成异常信息判别函数,通过待测网络运行数据与正常网络运行数据的特征对比,实现医院网络异常信息入侵检测。实验结果表明,算法能实现对医院网络异常信息入侵的高效检测,精准检测多类型网络入侵行为,为医疗机构网络运行提供安全保障。
