码分复用数字音频水印嵌入方案

结合人耳听觉特性，用扩频方法在音频信号中的听觉不敏感区域嵌入多路数字水印，从而实现码分复用．在对嵌入信息的检测中，除了少量系统参数外，数字水印的提取不需要原始信号，并且毋需精确同步．实验表明，该水印具有很好的隐蔽性；尤其是对常见攻击，MP3编码具有良好的稳健性．     

听觉线索引导大鼠空间定位

运用Morris水迷宫实验模式,研究听觉线索在大鼠进行空间定位时的作用.结果显示:听觉线索引导组和对照组动物在4 d内寻找平台的时间和错误率均显著下降.但与对照组动物相比,听觉线索引导组动物寻找隐藏平台的时间和错误率均较低,2组之间具有显著性差异(P<0.05).对动物的轨迹分析发现,听觉线索引导组和对照组动物在水池边缘区域分配的时间不同,提示2组动物寻找平台所用的策略不同.实验结果提示,大鼠能够利用单独的声音线索进行空间定位.     

用于语音识别中的SOFM矢量量化方法

该文讨论了神经网络语音识别系统中的ＫｏｈｏｎｅｎＳＯＦＭ神经网络的矢量量化（ＶＱ）的原理与过程,着重解决了其在实际应用时的若干问题,包括网络大小,学习步幅函数以及矢量量化过程中的公平竞争学习的控制函数的选定。过讨论了基于听觉模型的声学特性的提取与处理,这与ＶＱ性能息息相关。系统应用的实验表明,该神经网络在语音识别系统中具有良好性能。     

脑干听觉诱发电位波形分析建模、验证与算法优化

脑干听觉诱发电位是声觉器官受刺激后产生的一种生物电，反映了相应感觉通路及神经元群的活动，可用作听力阈值的客观判断，也可对多种耳疾和脑部病变作出诊断，因而成为当今临床医学和生物医学信号处理中的一个重要课题．文中介绍了脑干听觉诱发电位潜伏期（Ｌ）与刺激声强（Ｉ）之间关系曲线的作用，及其拟合建模和回归算法优化，还用实测数据对选定的拟合曲线模型进行了回归方差分析验证．     

鼠耳蝠下丘听神经元对超声刺激的反应特性

实验在５只鼠耳蜗上进行，共观察了２２７个对超声刺激发生反应的下丘听神经元。这些神经元听反应的最佳频率在１４．３－７６．２ｋＨｚ之间；潜伏期在３．０－１２．０毫秒之间，多数神经元（７９．３％）为５．０－７．０毫秒；最低阈值位于－２０．０－７０．０ｄＢ ＳＰＬ之间；多数神经元（８２．０５％）的调谐曲线为宽阔型，少数（１７．９５％）为狭窄型；反应最佳频率沿下丘背腹轴呈明显有序地排列。     

A novel audio watermarking scheme using multiscale wavelet modulation

A novel audio watermarking scheme to embed robust and inaudible watermarks for the purpose of copyright protection is proposed. The key innovation is to add time-frequency redundancy into watermark signals by multiscale wavelet modulation. In order to maximize the watermarking strength within perceptual constraints, the signals synthesized from different scales are masked using a frequency auditory model, respectively, and then intergrated to form the final watermark signal. The detection structure is built using the redundancy in watermark signals, and the performance is further enhanced by modeling the statistical behaviors of wavelet coefficients as generalized Gaussian distribution. The use of original audio signal is not required in watermark detection. The experimental results show that our approach can achieve not only good transparency but also satisfying robustness to common audio manipulations.     

For whom the bell tolls? DING proteins in health and disease

DING proteins, identified mainly by their eponymous N-terminal sequences, are ubiquitous in living organisms. Amongst bacteria, they are common in pseudomonads, and have been characterised with respect to genetics and structure. They form part of a wider family of phosphate-binding proteins, with emerging roles in phosphate acquisition and pathogenicity. Many DING proteins have been isolated in eukaryotes, in which they have been associated with very diverse biological activities, often in the context of possible signalling roles. Disease states in which DING proteins have been implicated include rheumatoid arthritis, lithiasis, atherosclerosis, some tumours and tumour-associated cachexia, and bacterial and viral adherence. Complete genetic and structural characterisation of eukaryotic DING genes and proteins is still lacking, though the phosphate-binding site seems to be conserved. Whether as bacterial proteins related to bacterial pathogenicity, or as eukaryotic components of biochemical signalling systems, DING proteins require further study. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

基于听觉场景分析的近讲语音增强算法

针对近讲场景,提出一种双麦克近讲语音增强算法。该算法基于耳间延时差(ITD)、耳间强度差(IID)特征来区分目标语音,利用声学掩蔽效应,实现目标语音对背景噪声的分离降噪。与传统的单麦克增强方法相比,该算法可消除多种类型噪声且对语音造成的损伤较小。实验表明:该算法能将8～33dB的白噪声、音乐噪声、广播噪声3种噪声类型的带噪语音的信噪比提高到36dB以上,同时保持较高的目标语音可懂度。对于冲击噪声的带噪语音也具有较好的降噪效果。     

A Novel Digital Audio Watermarking Scheme in the Wavelet Domain

We present a novel quantization-based digital audio watermarking scheme in wavelet domain. By quantizing a host audio‘s wavelet coefficients (Integer Lifting Wavelet Transform ) and utilizing the characteristics of human auditory system ( HAS), the gray image is embedded using our watermarking method. Experimental results show that the proposed watermarking scheme is inaudible and robust against various signal processing such as noising adding, lossy compression, low pass filtering, re-sampling, and re-quantifying.     

基于独立分量分析的失匹配负波快速提取

失匹配负波(MM N)是一种由刺激变化所诱发的听觉诱发电位成分,其过低的信噪比造成检测和提取比较困难。提出利用独立分量分析(ICA)方法对多导听觉诱发电位信号进行多次分解,根据MM N产生的生理机制及其信号特征,设计合理的独立分量选取原则,提取MM N。该方法通过仿真实验验证,能有效提高信噪比。在真实数据的处理中,仅用传统方法20%左右的实验时间,实现MM N成分波的提取。这将促进MM N在认知神经科学及临床上的应用。