Blind Speech Watermarking Method with Frame Self-Synchronization Based on Spread-Spectrum Using Linear Prediction Residue

State-of-the-art speech watermarking techniques enable speech signals to be authenticated and protected against any malicious attack to ensure secure speech communication. In general, reliable speech watermarking methods must satisfy four requirements: inaudibility, robustness, blind-detectability, and confidentiality. We previously proposed a method of non-blind speech watermarking based on direct spread spectrum (DSS) using a linear prediction (LP) scheme to solve the first two issues (inaudibility and robustness) due to distortion by spread spectrum. This method not only effectively embeds watermarks with small distortion but also has the same robustness as the DSS method. There are, however, two remaining issues with blind-detectability and confidentiality. In this work, we attempt to resolve these issues by developing an approach called the LP-DSS scheme, which takes two forms of data embedding for blind detection and frame synchronization. We incorporate blind detection with frame synchronization into the scheme to satisfy blind-detectability and incorporate two forms of data embedding process, front-side and back-side embedding for blind detection and frame synchronization, to satisfy confidentiality. We evaluated these improved processes by carrying out four objective tests (PESQ, LSD, Bit-error-rate, and accuracy of frame synchronization) to determine whether inaudibility and blind-detectability could be satisfied. We also evaluated all combinations with the two forms of data embedding for blind detection with frame synchronization by carrying out BER tests to determine whether confidentiality could be satisfied. Finally, we comparatively evaluated the proposed method by carrying out ten robustness tests against various processing and attacks. Our findings showed that an inaudible, robust, blindly detectable, and confidential speech watermarking method based on the proposed LP-DSS scheme could be achieved.     

Blind 2-D Angles of Arrival Estimation for Distributed Signals Using L-Shaped Arrays

Most existing two dimensional（2-D）angles of arrival（AOAs）estimation methods are based on the assumption that the signal sources are point sources.However,in mobile communications,local scattering in the vicinity of the mobile results in angular spreading as seen from a base station antenna array.In this paper,we consider the problem of estimating the 2-D AOAs of spatially distributed sources.First we perform blind estimation of the steering vectors by exploiting joint diagonalization,then the 2-D AOAs are obtained through two fast Fourier transforming of the estimated steering vectors.Simulations are carried out to illustrate the performance of the method.     

改进的萤火虫群优化算法及其非线性盲源分离

摘要：根据萤火虫算法的特点,针对萤火虫算法较早进入局部收敛的不足进行改进,引入了“挡板效应”的方法,扩大种群多样性,并提出了BGSO算法。在分析了非线性盲源分离模型的基础上,利用系统两次遍历萤火虫群,比较评价函数,获得最优解的方式。其有效性被仿真结果所证实。     

一种并行的软判决引导常数模盲均衡算法

介绍了一种常数模与软判决引导结合的盲均衡算法CMA SDD。该算法克服了CMA收敛速度慢、稳态误差大的缺点,同时可以纠正相位偏转。仿真表明,在高信噪比(SNR)条件下,两种算法的稳态均方误差相近,而CMA SDD算法的收敛速度更快;在低信噪比条件下,CMA SDD算法可以获得更快的收敛速度和更低的稳态均方误差。     

Proxy-cryptocurrency payment system

The decentralized cryptocurrency which was based on block chain has been thought the most successful one in history.In the system,public keys were used as the users’ accounts which guaranteed the anonymity in real transactions.However,all the transaction information was recorded in the block chain,it was a potential threat for users’ privacy which might leak the payment information.Moreover,to avoid double-spending,it was agreed that the transaction on the target block was valid only if another k blocks were generated after the target one.The long waiting time reduced the efficiency of the payment system.A model of payment system based on a proxy-cryptocurrency was proposed,and a solution based on blind signature techniques was proposed.The scheme introduced a proxy in the payment phase,by which transaction confirmation time could be reduced and the transaction efficiency could be improved.Meanwhile,the system implements better anonymity,namely as the privacy protection function.     

基于欠定盲分离的多目标微多普勒特征提取

连续波雷达多目标回波中多种微多普勒特征分离问题采用独立成分分析方法实现,该方法在使用中存在较大局限性,要求待分离的微多普勒特征之间必须是统计独立的,且仅局限于恰定和超定的方程组求解问题。然而,在多目标雷达观测场景下,雷达接收的混叠回波的个数通常少于目标的个数,各目标的微多普勒特征可能存在相关性。为此,提出了一种基于欠定盲分离的多目标回波微多普勒特征分离方法。该方法可以从少数原始混叠回波中分离出多个目标的微多普勒特征,对待分离的微多普勒特征限制性弱。通过数值仿真,证实了该方法的可行性。     

基于电力线信道的一类OFDM盲同步算法的改进

针对电力线通信中多普勒频移为零以及具有一定拓扑结构的电力线信道中由多径反射所产生的时延扩展较移动信道而言相对稳定的特点,这里在最大似然（ML）类算法的基础上,实现了基于电力线信道的改进的正交频分复用技术（OFDM）同步算法。该方法有效的弥补了ML类算法不适合具有多径效应的电力线信道的不足。理论分析和仿真结果表明,该算法在电力线信道中具有良好的定时估计和频率偏移估计性能,而且计算量减少。     

独立成分分析基本原理与发展

独立成分分析是为解决盲源分离问题发展起来的一种高效的信号处理方法,广泛应用于国民经济发展和国防军事科学的各个领域。系统介绍了独立成分分析的基本模型、假设条件、解的不确定性问题,总结了目标函数的建立依据,如非高斯性最大化、互信息极小化和极大似然估计等,并简要总结了近年出现的独立成分分析优化方法,最后对独立成分分析的难点问题和未来可能的发展方向进行了总结和展望。     

数字共焦显微技术及其处理算法的进展

数字共焦显微技术是一种新的共焦显微技术,其通过对三维样本显微图像的数字处理,获取高分辨率图像,无光漂白和毒化细胞现象,结构简单、价格便宜。简述了数字共焦显微技术及其进展,着重介绍了核心技术--去卷积算法及其特点:去模糊法速度很快,但易引入结构性假像,不宜用于测量和计算;线性复原法速度较快,复原效果较好,但会放大噪声和出现振铃;约束迭代法速度较慢,但复原能力强,分辨率高。各类算法在商业软件中都得到不同的应用。由于数字共焦显微技术的独有优势,随着去卷积算法的发展,数字共焦显微技术将获得更为广泛的应用。     

极值斜率经验模式分解结合独立分量分析的单通道盲分离

针对单通道盲分离领域先验信息不足的问题,提出了一种基于极值斜率经验模式分解和独立分量分析的单通道盲分离算法。首先通过极值斜率经验模式分解算法以不同尺度逐次分解混合信号的波动和趋势,得到一组固有模态函数。然后将其作为独立分量分析算法的输入信号,从得到的独立分量中萃取出与源信号相似的独立分量,通过重构算法恢复源信号,达到分离目的。实验信号采取仿真信号和实际信号,实验结果表明,该算法不需任何先验信息,鲁棒性强,能较快地得到良好的分离效果。