混沌直扩信号扩频序列盲估计

与传统直扩序列相比,混沌扩频序列具有非线性复杂度较高的优点,该优点同时也是盲估计混沌扩频序列的难点。针对这个难点,该文提出了非线性弹性反传神经网络盲估计方法,充分利用非线性神经网络能逼近任意非线性函数的特性,无须搜索信息码和扩频序列之间的同步点,能在较低的信噪比下准确盲估计混沌扩频序列。传统的神经网络使用中,神经网络的有用信息是网络的输出,而该文中则是输出层的权系数。侦察截获的混沌直扩信号同时用作神经网络的输入和期望输出,神经网络收敛后的输出层权系数就是混沌扩频序列的估计值。仿真结果证明了该方法的有效性。     

基于四阶累积量的稳健的通信信号盲分离算法

该文针对有噪环境中的通信信号盲分离问题,提出了一种在噪声环境下性能良好的盲分离算法,该算法将稳健的白化算法与四阶累积量矩阵的联合对角化相结合。仿真结果表明,该算法分离性能比一般的近似联合对角化(JAD)算法有很大改善,干信比可降低近10dB,而算法的运算量没有太多增加。     

一族新Bussgang类盲均衡算法

该文提出了一族新Bussgang类盲均衡算法统一形式的代价函数,该代价函数具有明确的数学意义,包括了经典的Decision-Directed算法,Sato算法,CMA算法及其变种。根据该代价函数,可以设计出新类型的Bussgang盲均衡算法,该文据此设计了两种新型的Bussgang盲均衡算法,仿真实验验证了这两种新算法的收敛性能。     

MC-CDMA系统中一种线性共轭MOE多用户检测算法

该文提出MC-CDMA系统下一种基于递归最小二乘(Recursive Least-Squares, RLS)的最小输出能量(Minimum Output Energy, MOE)噪声抑制线性共轭多用户检测算法.该算法定义了一种新的基于MOE准则的代价函数,同时将噪声子空间作为MOE代价函数的约束条件,设计了一种噪声抑制的线性共轭检测器,并采用RLS算法自适应得到权向量.所提算法将权向量和噪声子空间正交,消除了权向量中的噪声分量,并且利用了伪自相关矩阵的信息,从而提高了系统的性能.仿真结果证明了本文算法的有效性和优越性.     

A time-frequency blind separation method for underdetermined speech mixtures

The proposed Blind Source Separation method （BSS）, based on sparse representations, fuses time-frequency analysis and the clustering approach to separate underdetermined speech mixtures in the anechoic case regardless of the number of sources. The method remedies the insufficiency of the Degenerate Unmixing Estimation Technique （DUET） which assumes the number of sources a priori. In the proposed algorithm, the Short-Time Fourier Transform （STFT） is used to obtain the sparse representations, a clustering method called Unsupervised Robust C-Prototypes （URCP） which can accurately identify multiple clusters regardless of the number of them is adopted to replace the histogram-based technique in DUET, and the binary time-frequency masks are constructed to separate the mixtures. Experimental results indicate that the proposed method results in a substantial increase in the average Signal-to-Interference Ratio （SIR）, and maintains good speech quality in the separation results.     

A weighted general discrete fourier transform for the frequency-domain Blind Source Separation of Convolutive Mixtures

This letter deals with the frequency domain Blind Source Separation of Convolutive Mixtures （CMBSS）. From the frequency representation of the ＂overlap and save＂, a Weighted General Discrete Fourier Transform （WGDFT） is derived to replace the traditional Discrete Fourier Transform （DFT）. The mixing matrix on each frequency bin could be estimated more precisely from WGDFT coefficients than from DFT coefficients, which improves separation performance. Simulation results verify the validity of WGDFT for frequency domain blind source separation of convolutive mixtures.     

TSV三维封装缺陷激光主动检测分类与量化

硅通孔(TSV)三维封装因其独特工艺而受到广泛关注,然而其内部缺陷无法被直接观测成为目前的检测难题。为了对TSV三维封装内部缺陷进行检测,提出了一种基于激光主动激励的内部缺陷分类与量化方法。通过红外激光主动热源施加到TSV三维封装结构表面,激发TSV内部缺陷的外部温度分布响应,通过理论与仿真分析,掌握缺陷特征在主动激励下的表现规律；构建卷积神经网络对缺陷样本信息进行训练,实现内部缺陷的分类识别与量化。试验表明,该方法能在不损坏样品的前提下有效对内部缺陷进行识别分类及量化,准确率可达95.56%。     

一种采用微小通孔的双层布线技术

文中介绍了分别采用聚酰亚胺和 CVD Si O2 作层间介质 ,进行 2 μm× 2 μm通孔的刻蚀和铝双层布线 ,其成品率均可达到 1 0 0 % ,介质对一次铝的覆盖完整率可达 95%以上 ,层间绝缘电压大于 2 50 V     

Dual-branch vision transformer for blind image quality assessment

Blind image quality assessment (BIQA) has always been a challenging problem due to the absence of reference images. In this paper, we propose a novel dual-branch vision transformer for BIQA, which simultaneously considers both local distortions and global semantic information. It first extracts dual-scale features from the backbone network, and then each scale feature is fed into one of the transformer encoder branches as a local feature embedding to consider the scale-variant local distortions. Each transformer branch obtains the context of global image distortion as well as the local distortion by adopting content-aware embedding. Finally, the outputs of the dual-branch vision transformer are combined by using multiple feed-forward blocks to predict the image quality scores effectively. Experimental results demonstrate that the proposed BIQA method outperforms the conventional methods on the six public BIQA datasets.     

2.5D硅转接板关键电参数测试技术研究

硅转接板是3D IC中实现高密度集成的关键模块,获取其技术参数对微系统的设计至关重要.以实际研制的一种2.5D硅转接板为研究对象,对大马士革铜布线(Cu-RDL)、硅通孔(TSV)关键电参数的测试结构与测试方法进行了研究,并对TSV电参数测试结构的寄生电容进行了分析.研究结果表明,研制的2.5D硅转接板中10 μm×8...