The aim of this work is the development of a steganographic technique for the MP3 audio format, which is based on the Peak Shaped Model algorithm used for JPEG images. The proposed method relies on the statistical pro...The aim of this work is the development of a steganographic technique for the MP3 audio format, which is based on the Peak Shaped Model algorithm used for JPEG images. The proposed method relies on the statistical properties of MP3 samples, which are compressed by a Modified Discrete Cosine Transform (MDCT). After the conversion of MP3, it’s possible to hide some secret information by replacing the least significant bit of the MDCT coefficients. Those coefficients are chosen according to the statistical relevance of each coefficient within the distribution. The performance analysis has been made by calculating three steganographic parameters: the Embedding Capacity, the Embedding Efficiency and the PSNR. It has been also simulated an attack with the Chi-Square test and the results have been used to plot the ROC curve, in order to calculate the error probability. Performances have been compared with performances of other existing techniques, showing interesting results.展开更多
针对分布式电源和新型负荷容量累积造成负荷影响因素多元化和不确定性特性增强的问题,文中提出一种采用记忆神经网络和曲线形状修正的负荷预测方法。在负荷峰值预测中,采用最大信息系数计算负荷峰值与影响因素的非线性相关性,实现对输...针对分布式电源和新型负荷容量累积造成负荷影响因素多元化和不确定性特性增强的问题,文中提出一种采用记忆神经网络和曲线形状修正的负荷预测方法。在负荷峰值预测中,采用最大信息系数计算负荷峰值与影响因素的非线性相关性,实现对输入特征的筛选;综合考虑负荷峰值序列的长短期自相关性和输入特征与负荷峰值的不同程度相关性,结合Attention机制和双向长短时记忆(bidirectional long short-term memory,BiLSTM)神经网络建立负荷峰值预测模型。在负荷标幺曲线预测中,通过误差倒数法组合相似日和相邻日,建立负荷标幺曲线预测模型;针对预测偏差的非平稳特征,利用自适应噪声的完全集成经验模态分解和BiLSTM网络建立误差预测模型,对曲线形状进行修正。应用中国北方某城市的区域电网负荷数据为算例,验证了所提模型的有效性。展开更多
文摘The aim of this work is the development of a steganographic technique for the MP3 audio format, which is based on the Peak Shaped Model algorithm used for JPEG images. The proposed method relies on the statistical properties of MP3 samples, which are compressed by a Modified Discrete Cosine Transform (MDCT). After the conversion of MP3, it’s possible to hide some secret information by replacing the least significant bit of the MDCT coefficients. Those coefficients are chosen according to the statistical relevance of each coefficient within the distribution. The performance analysis has been made by calculating three steganographic parameters: the Embedding Capacity, the Embedding Efficiency and the PSNR. It has been also simulated an attack with the Chi-Square test and the results have been used to plot the ROC curve, in order to calculate the error probability. Performances have been compared with performances of other existing techniques, showing interesting results.
文摘针对分布式电源和新型负荷容量累积造成负荷影响因素多元化和不确定性特性增强的问题,文中提出一种采用记忆神经网络和曲线形状修正的负荷预测方法。在负荷峰值预测中,采用最大信息系数计算负荷峰值与影响因素的非线性相关性,实现对输入特征的筛选;综合考虑负荷峰值序列的长短期自相关性和输入特征与负荷峰值的不同程度相关性,结合Attention机制和双向长短时记忆(bidirectional long short-term memory,BiLSTM)神经网络建立负荷峰值预测模型。在负荷标幺曲线预测中,通过误差倒数法组合相似日和相邻日,建立负荷标幺曲线预测模型;针对预测偏差的非平稳特征,利用自适应噪声的完全集成经验模态分解和BiLSTM网络建立误差预测模型,对曲线形状进行修正。应用中国北方某城市的区域电网负荷数据为算例,验证了所提模型的有效性。
