A Robust Watermarking Scheme Using Sequency-ordered Complex Hadamard Transform

This paper presents a robust phase watermarking scheme for still digital images based on the sequency-ordered complex Hadamard transform (SCHT). The transform matrix of the SCHT exhibits sequency ordering which is analogous to frequency in the discrete Fourier transform (DFT). Hence, sequency-based image analysis can be performed for image watermarking while providing simple implementation and with less computational complexity for computation of the transform. As the SCHT coefficients are complex numbers which consist of both magnitudes and phases, they are suited to adopt phase modulation techniques to embed the watermark. In this proposed scheme, the phases of the SCHT coefficients in the sequency domain are altered to convey the watermark information using the phase shift keying (PSK) modulation. Low amplitude block selection (LABS) is used to enhance the imperceptibility of digital watermark, and amplitude boost (AB) method is employed to improve the robustness of the watermarking scheme. Spread spectrum (SS) technique is adopted to increase the security of watermark against various unintentional or intentional attacks. In order to demonstrate the effectiveness of the proposed watermarking scheme, simulations are conducted under various kinds of attacking operations. The results show that the proposed scheme is able to sustain a series of attacks including common geometric transformations such as scaling, rotating, cropping, painting, and common image-processing operations such as JPEG compression, low-pass filtering, sharpening, noising and phase perturbation, etc. Comparisons of the simulation results with the other schemes are also mentioned and the results reveal that the proposed scheme shows better robustness.     

Conjugate Symmetric Sequency-Ordered Complex Hadamard Transform

A new transform known as conjugate symmetric sequency-ordered complex Hadamard transform (CS-SCHT) is presented in this paper. The transform matrix of this transform possesses sequency ordering and the spectrum obtained by the CS-SCHT is conjugate symmetric. Some of its important properties are discussed and analyzed. Sequency defined in the CS-SCHT is interpreted as compared to frequency in the discrete Fourier transform. The exponential form of the CS-SCHT is derived, and the proof of the dyadic shift invariant property of the CS-SCHT is also given. The fast and efficient algorithm to compute the CS-SCHT is developed using the sparse matrix factorization method and its computational load is examined as compared to that of the SCHT. The applications of the CS-SCHT in spectrum estimation and image compression are discussed. The simulation results reveal that the CS-SCHT is promising to be employed in such applications.     

Real-Time Video Compression Algorithm for Hadamard Transform Processing

A real-time digital video processor using Hadamard transform techniques to reduce video bandwidth is described. The processor can be programmed with different parameters to investigate various algorithms for bandwidth compression. The processor is also adaptive in that it can select different parameter sets to trade-off spatial resolution for temporal resolution in the regions of the picture that are moving. Algorithms used in programming the system are described along with results achieved at various levels of compression. The algorithms relate to spatial compression, temporal compression, and the adaptive selection of parameter sets.     

应用于信号处理的Fourier变换与小波变换

在分析Fourier变换与小波变换异同点的基础上,对它们在不同类型信号的处理过程中的应用进行了探讨．并给出一个检测故障点的仿真实例,证明了小波变换的优越性．     

基于Hadamard矩阵变换降低OFDM系统PAPR的新算法

本文研究了一种基于Hadamard变换降低OFDM系统PAPR的新算法,该算法扩展了传统系统的星座点,减小了频域符号间的相关性,其编解码算法简便,易于实现。文中分析了该算法的基本原理,同时仿真结果表明,采用该算法其PAPR可以比传统方法降低3-4dB;并且可以与其它方法联合使用,从而进一步降低PAPR。     

基于小波变换的超声波含噪信号处理

超声波流量计测量气体或液体流量时,传感探头接收的超声波信号中夹杂了大量噪声,它将会影响信号的分析和流量的测量.而传统方法无法刻画超声波信号的非平稳特性并准确去噪,为克服传统方法的不足,采用小波变换理论,结合阈值去噪法,通过Matlab仿真实验,可得去噪后的超声波信号,从而验证小波变换可用于超声波信号去噪的处理.     

双正交小波在陀螺信号去噪中的应用

本文在用双正交小波对陀螺信号进行不同尺度分解的基础上,结合传统的信号分析方法,得出小波系数是由噪声产生的,从而提出合适的小波去噪方法。本方法在应用中得到较好的去噪效果。     

Chirp-z变换在雷达信号处理中的应用

雷达信号处理算法中大多数采用FFT方法测量频率,如果提高测频精度需增加FFT点数,增加FFT点数的实质是在整个单位圆（即整个距离谱）上均匀增加频域采样点数,从而造成运算量的成倍增加。Chirp-z变换可以实现对回波频谱中的某段进行局部细化,从而在采样点数、运算量增加不多的情况下,大大提高雷达的测量精度。     

基于连续小波变换的雷达信号处理

在步进频率雷达一维距离成像技术中,经典的傅里叶变换算法受到距离分辨率的限制,并且存在较高的副瓣电平。针对这一问题,本文提出将连续小波变换算法用于频率步进雷达的一维距离成像。该方法在保持高距离分辨率的同时,可有效降低回波信号的副瓣电平。     

基于围线积分引理的信号变换域分析方法

提出了一种直接利用连续时间信号的双边LT来计算相应样值序列的双边ZT的方法。首先,基于围线积分引理,研究了s域卷积运算问题,给出了利用区左极点或区右极点计算s域卷积的留数方法;然后,依据连续时间非周期信号的ILT导出了非周期序列的IZT,给出了利用区外极点计算有终序列的IZT及计算z域卷积的留数方法;最后,解决了利用连续时间信号的双边LT来计算时域卷积信号和乘积信号相应样值序列的双边ZT的问题。     

Signal Processing Using Mutual Information

The Darbellay-Vajda algorithm was used to develop a skeletonized approximation to a joint probability density of sampled data. The approximation is presented as a collection of non-overlapping multi-dimensional cuboids, having varying sizes, locations, and probabilities in sample space. It is already known that a mutual information value can be extracted from this collection. This paper demonstrates that the joint density has a far wider range of application in exploring Bayesian and conditional probability distributions among the observations. While the examples provided show only autonomous data modeling, categorical data is easily input as an additional independent variable for supervised training purposes. Though the mathematical fundamentals of the algorithm are hardly straightforward, the associated computation load is low, and the overall flexibility of the technique points to the possibility of attractive new algorithms for statistical signal processing in numerous areas such as machine learning, pattern recognition, and nonlinear filtering     

超复数域小波变换的显著性检测

针对现有频域显著性检测方法得到的显著区域不完整的问题,该文提出一种多尺度分析的频率域显著性检测方法。首先由输入图像特征通道信息构建4元超复数,然后通过小波变换对4元超复数域中幅度谱进行多尺度分解,计算生成多尺度下的视觉显著图,最后由评价函数选出效果较好显著图合成最终视觉显著图。实验结果表明,该文方法能够有效地抑制背景干扰,快速、精确地找到完整的显著目标,具有较高的检测精确度。     

基于小波包变换的信号谱峰检测算法

提出了一种新的基于小波包变换的信号谱峰检测算法,主要思想是利用小波包变换的特点,对信号功率谱进行平滑处理,突出谱峰的特征点（起点、顶点和终点）,然后对其进行三层小波包变换,提取相应细节系数的特征点来估计谱峰的起点、顶点和终点,从而完成谱峰的检测。该方法的特点是无需信号的任何先验信息,是一种盲处理算法。仿真结果表明,信噪比不低于5dB的情况下,信号特征点检测的归一化均方误差（NMME）低于6‰,其性能比传统基于差分的方法有明显的优势。     

基于小波变换的多项式相位信号检测

N阶消失矩的小波能够消去n-1阶多项式。本文用具有不同消失矩小波,依次消去多项式相位信号不同阶次的相位向,实现单个多项式相位信号的检测。仿真结果表明,这一算法能够有效地检测多项式相位信号。     

超宽带信号时域动目标处理方法

首先简要介绍了超宽带（UWB）信号的基本特性及其在实现目标探测中的应用优势和应用前景,然后从时域处理的角度,阐述了对UWB回波信号实现时移相参积累和隔周期相关处理的方法,并通过试验研究,分析了时域处理方法的优点及不足。     

一种基于Hilbert-Huang变换的雷达回波精细处理技术

某新型雷达通过提取回波中人体的心跳和呼吸信号,达到探测人体的目的,在医学治疗、灾后搜救、反恐作战等领域具有广阔的应用前景.由于目标信号无论在时域或频域上强度都很微弱,传统的雷达信号处理方法很难将其从回波中提取出来,文中基于Hilbert-Huang变换(HHT)方法提出了一种新的精细处理雷达回波的技术,对该型号雷达的实录数据的处理结果表明,上述新技术能够有效地提取出目标的精细特征.     

Slant Plane CSAR Processing Using Householder Transform

Fourier analysis-based focusing of synthetic aperture radar (SAR) data collected during circular flight path is a recent advancement in SAR signal processing. This paper uses the Householder transform to obtain a ground plane circular SAR (CSAR) signal phase history from the slant plane CSAR phase history by inverting the linear shift-varying system model, thereby circumventing the need for explicitly computing a pseudo-inverse. The Householder transform has recently been shown to have improved error bounds and stability as an underdetermined and ill-conditioned system solver, and the Householder transform is computationally efficient.     

Hadamard变换和Haar变换谱系数的图形转换法

本文根据Hadamard变换谱系数（had谱系数）与布尔列矢量的关系以及Haar为换谱系数（ha谱系数）与布尔列矢量的关系,提出了had谱系数与ha谱系数之间的图形转换方法,并举例说明转换过程,该方法揭示了系数图与ha系数图之间的内在联系,具有简单,直观的特点。     

High-Efficiency Soft-Error-Tolerant Digital Signal Processing Using Fine-Grain Subword-Detection Processing

The soft error problem in digital circuits is becoming increasingly important as the IC fabrication technology progresses from the deep submicrometer scale to the nanometer scale. This paper proposes a subword-detection processing (SDP) technique and a fine-grain soft-error-tolerance (FGSET) architecture to improve the performance of the digital signal processing circuit. In the SDP technique, the logic masking property of the soft error in the combinational circuit is utilized to mask the single-event upset (SEU) caused by disturbing particles in the inactive area. To further improve the performance, the masked portion of the datapath can be used as the estimation redundancy in the algorithmic soft-error-tolerance (ASET) technique. This technique is called subword-detection and redundant processing (SDRP). In the FGSET architecture, the soft error in each processing element (fine grain) can be recovered by the arithmetic datapath-level ASET technique. Analysis of the fast Fourier transform processor example shows that the proposed FGSET architecture can improve the performance of the coarse-grain SET (CGSET) by 8.5 dB. The low-cost SDP technique (1.03$ times$) yields a noise reduction of 5.3 dB over the CGSET approach (1.40 $ times$), while the efficient SDRP I (1.57$ times$) and SDRP II (1.88$ times$ ) techniques outperform the CGSET approach by 24.5 and 30.5 dB, respectively.