On Certain Pathwise Properties of the Sliding-Window Lempel–Ziv Algorithm

We derive several almost-sure results related to the sliding-window Lempel-Ziv (SWLZ) algorithm. A principal result is a path-wise lower bound to the redundancy equal to 1/2hlog₂log ₂n_w/log₂n_w in the main term, where n_w is the sliding window size. This bound is off by a factor of two from the main term in the lower bound of A. J. Wyner and the work of Yang and Kieffer, which hold in the expected sense for the fixed-database Lempel-Ziv algorithm (FDLZ). Another aspect of the present work studies the asymptotic behavior of the ratio of the number of phrases to the length of the parsed string for any finite sliding window size; in here we exploit the theory of asymptotic mean stationary processes of Gray and Kieffer and some results of Kieffer and Rahe. In all cases it is assumed that the source is stationary and that in the most restrictive case it is an irreducible and aperiodic Markov chain; some of the results hold for sources that have exponential rates for entropy and more generally for the ergodic setting     

Successive Wyner–Ziv Coding Scheme and Its Application to the Quadratic Gaussian CEO Problem

In this paper, we introduce a distributed source coding scheme called successive Wyner-Ziv coding. We show that every point in the rate region of the quadratic Gaussian CEO problem can be achieved via successive Wyner-Ziv coding. The concept of successive refinement in single source coding is generalized to the distributed source coding scenario, which we refer to as distributed successive refinement. For the quadratic Gaussian CEO problem, we establish a necessary and sufficient condition for distributed successive refinement, where the successive Wyner-Ziv coding scheme plays an important role.     

改进模拟退火算法在矢量量化编码中的应用

为了提高模拟退火算法的最终解的质量,文中对控制算法进程的冷却进度表进行了优化选取,尤其在控制马尔可夫链长方面,给出了依据算法搜索过程的反馈信息来控制马尔可夫链长的方法.将该算法与LBG算法相结合,应用于矢量量化图像编码,既保持了模拟退火对初始码书依赖性小、不容易陷入局部极值的优点,又具备LBG算法的易于实现和计算量小的特点.仿真实验表明,该算法提高了码书的编码性能.     

一种新的二维特征抽取算法及应用

二维主成分分析方法是直接利用二维图像来构建方差矩阵的。为了充分利用样本类别信息,文章以类间散布矩阵特征向量作为投影方向进行特征抽取。首先用2DPCA先作一次横向压缩,对抽取出的特征矩阵再用2DPCA作一次纵向压缩。与传统二维主成分算法比较,极大压缩了特征的维数,加快了分类速度,提高了识别率。用ORL人脸数据库进行了实验验证,证明了本方法的可行性。     

A Cost-Shared Quantization Algorithm and Its Implementation for Multi-Standard Video Codecs

Due to the growing demand of digital convergence, there is a need to have a video encoder/decoder (codec) that is capable of supporting multiple video standards on a single platform. High Efficiency Video Coding (HEVC), successor to H.264/MPEG-4 AVC, is a new standard under development that aims to substantially improve coding efficiency compared to AVC High Profile. This paper presents an efficient architecture based on a resource sharing strategy that can perform the quantization operation of the emerging HEVC encoder and six other video encoders: H.264/AVC, AVS, VC-1, MPEG-2, MPEG-4, and Motion JPEG (MJPEG). Since HEVC is still in the drafting stage, the proposed architecture is designed in such a way that any final changes can be accommodated into the design. The proposed quantizer architecture is completely division-free, as the division operation is replaced by shift and addition operations for all the codecs. The design is implemented on an FPGA and later synthesized in CMOS 0.18 μm technology. While working at 190 MHz, the design can decode a 1080p HD video at up to 61 frames per second. The multi-codec architecture is also suitable for low-cost VLSI implementation.     

A Fast Encoding Algorithm for Vector Quantization Using Difference Pyramid Structure

This paper proposed a fast vector quantization encoding algorithm called difference pyramid search (DPS). According to the formation of the difference pyramid and partial distortion elimination, a rejection test inequality is derived to progressively reject a lot of nonclosest code words as early as possible. Experimental results show that the proposed DPS algorithm outperforms other pyramid-based fast search algorithms, including mean pyramid search, L2-norm pyramid search, and mean-variance pyramid search.     

一种自适应线谱对滤波器的终点误差LMS算法及其学习特性

本文提出了一种计算线谱对（LSP）系数的新算法．该算法以最小均方（LMS）误差型算法为基础，梯度计算使用系统终点误差。对接收到的语音观测样本在一个时序的基础进行迭代更新计算，直接产生LSP系数，形成一个LMS算法的自适应LSP滤波器。实验结果表明，该算法与其它自适应滤器的LMS算法比较，具有更高的收敛率和较低的失调。     

新型自适应Kalman滤波算法及其应用

为防止滤波发散和提高系统的实时性,提出了一种新的自适应Kalman滤波算法.该算法利用滤波异常判据获得一个滤波状态因子,通过滤波状态因子确定量测噪声协方差阵的值,在线调整噪声的统计特性实现自适应滤波.将该算法应用到惯导/双星组合导航系统中,并和常规Kalman滤波和简化的Sage-Husa自适应滤波算法进行仿真比较.仿真结果表明,在滤波精度与简化Sage-Husa自适应滤波相当的情况下,新算法简化了运算,提高了实时性.     

一种基于双正交小波变换和格型矢量量化的视频编码算法

本文提出了基于双正交小波变换（ｂｉｏｒｔｈｏｇｏｎａｌｗａｖｅｌｅｔｔｒａｎｓｆｏｒｍ）和格型矢量量化（ＬＶＱｌａｔｔｉｃｅｖｅｃｔｏｒｑｕａｎｔｉｚａｔｉｏｎ）的视频编码算法。在该方案中，小波变换将图像分解成多分辨率（ｍｕｌｔｉｒｅｓｏｌｕｔｉｏｎ）的子带图像，多分辨率运动估值（ＭＲＭＥ，ｍｕｌｔｉｒｅｓｏｌｕｔｉｏｎｍｏｔｉｏｎｅｓｔｉｍａｔｉｏｎ）技术实现子带图像的帧间预测，格型矢量量化对预测差值子带图像进行编码，从而获得了性能较好的活动图像编码新算法。     

模糊强化学习型的图像矢量量化算法

本文给出了一种新的图像矢量量化码书的优化设计方法.传统矢量量化方法只考虑了码字与训练矢量之间的吸引影响,所以约束了最优解的寻解空间.本文提出了一种新的学习机理--模糊强化学习机制,该机制在传统的吸引因子基础上,引入新的排斥因子,极大地释放了吸引因子对最优解的寻解空间的约束.新的模糊强化学习机制没有采用引入随机扰动的方法来避免陷入局部最优码书,而是通过吸引因子和排斥因子的合力作用,较准确地确定了每个码字的最佳移动方向,从而使整体码书向全局最优解靠近.实验结果表明,基于模糊强化学习机制的矢量量化算法始终稳定地取得显著优于模糊K-means算法的性能,较好地解决了矢量量化中的码书设计容易陷入局部极小和初始码书影响优化结果的问题.     

一种严格最大熵谱估计法的递推算法

本文提出了基于一种更严格最大熵谱估计的快速递推算法。讨论了当数据长度有限时，为满足最大熵谱估计的四个近似等价条件，所提出的严格目标函数。在此基础上，通过使目标函数达到极小，用递推法估计出各阶反射系数，然后由Levinson递推得到最大熵谱参数的估计值。该算法算法稳定，快速。计算机仿真表明，此估计方法具有良好的估计质量。     

一种基于信息融合的滤波算法及其应用

本文从组合导航系统研究的角度出发,提出了一种应用卡尔曼滤波技术建立多传感器信息融合系统的方法,该方法克服了以往存在的局部滤波器和全局滤波器具有相同数学模型的缺点,增强了算法的通用性.文中从概念理解、模型建立、系统结构等方面作了详细的分析,并针对GPS/INS组合导航系统进行了仿真.结果表明:该算法对提高导航系统的精度和运算速度是行之有效的.     

利用缓存加快量化数据取得的编码和解码方法

提出一种在音频算法中利用音频帧间与帧内的相关性,用缓存来加快量化数据取得的编码和解码方法.这种方法可以减少量化数据时重复的运算量.从而有效地提升编码与解码的计算速度,保证在原有量化条件下,在原有音频质量不变的基础上,减少比特数的使用量并降低解码端的运算量从而节省解码时间.     

基于颜色与线段的图像轮廓提取算法

传统二维图像轮廓识别算法通常是在图像中找到边缘,根据设定的条件将边缘像素组合起来形成轮廓。针对边缘检测算法通常需要对不同的图像设定不同的阈值,对不同类型的图像很难找出统一的阈值的问题,文中提出了一种同时利用图像中颜色与线段信息的彩色图像轮廓提取算法,算法采用自顶向下的颜色空间融合和自底向上的线段检测的方法,在初步获取边缘信息之后,综合利用检测结果生成目标的轮廓。算法的优点在于不需要进行阈值调整,实验表明:该方法可以有效地提取彩色图像中的目标轮廓。     

空域相关滤噪法的改进及用于红外光谱信号处理

基于Mallat 等提出的空域相关去噪法,提出了一种新的自适应小波滤噪法。它具有空域相关法的优点,同时克服了空域相关法的缺点,对信号中的噪声进行了最大限度的抑制而又保留了信号的主要细节。仿真计算和分析表明了此算法的有效性。     

彩色图像特征空间变换的新算法及其应用

本文提出了一种彩色图像特征空间变换算法.该算法基于高维形象几何与仿生信息学理论,根据人眼特性,利用彩色图像中彩色信息的变化进行特征空间变换,能够提取出不受光源影响的图像特征.在彩色图像人脸检测应用中,与常见的肤色分割方法不同,该算法不需对肤色建模,不对彩色图像进行非线性彩色空间变换,而是直接将彩色原图变换到特征空间,在特征空间中定位平均脸特征数据的最佳匹配点.本文最后将该算法应用于复杂光源彩色图像的人脸检测中,实验结果验证了算法的有效性和鲁棒性,具有明显的应用价值.     

一种有监督的LPP算法及其在人脸识别中的应用

为了提高局部保持投影算法(Locality Preserving Projections,LPP)对光照、姿态等外部因素的鲁棒性,该文对传统的LPP算法进行改进,提出了一种有监督的LPP(SLPP)方法。首先对LPP子空间进行判别分析,然后选择主要反应类内差异的基向量来构造子空间,最后在子空间上进行识别。通过Havard人脸库和Umist人脸库上的实验,结果表明该方法能够对光照和姿态的变化具有一定的鲁棒性和较高的识别率,比传统的LPP方法和其它子空间分析法识别率提高了10%以上。     

A New Overlap Save Algorithm for Fast Block Convolution and Its Implementation Using FFT

Convolution of data with a long-tap filter is often implemented by overlap save algorithm (OSA) using fast Fourier transform (FFT). But there are some redundant computations in the traditional OSA because the FFT is applied to the overlapped data (concatenation of previous block and the current block) while the DFT computations are recursive. In this paper, we first analyze the redundancy by decomposing the OSA into two processes related to the previous and current block. Then we eliminate the redundant computations by introducing a new transform which is applied only to the current data, not to the overall overlapped data. Hence the size of transform is reduced by half compared to the traditional OSA. The new transform is in the form of DFT and it can be implemented by defining a new butterfly structure. However we implement it by a cascade of twiddle factor and conventional FFT in this paper, in order to use the FFT libraries in PC and DSP. The computational complexity in this case is analyzed and compared with the existing methods. In the experiment, the proposed method is applied to several block convolutions and partitioned-block convolutions. The CPU time is reduced more than expected from the arithmetic analysis, which implies that the reduced transform size gives additional advantage in data manipulation.     

直接线性图嵌入算法及其在人脸识别中的应用

图嵌入算法使用无向有权图来描述数据集的流形结构,目前许多流形学习算法都可统一到这个框架下。线性图嵌入算法(LGE)在高维小样本应用中往往会遇到的奇异值问题,因此需把数据集预先投影到PCA子空间,往往会丢失了一些有用的信息。本文提出了一种直接的线性图嵌入算法(DLGE),可直接从原始数据集中提取特征。此外DLGE算法相对于基于迭代的正交化算法,在最小二乘意义下对截断的征向量进行正交化处理,计算简便有效。在多个人脸数据库库上的仿真结果表明,相对于传统算法,DLGE算法具有更强的人脸表征能力,更好的分类性能,且更加鲁棒。     

一种新自适应滤波快速算法及其 在多路回波消除中的应用

本文提出了一种新的自适应滤波算法,该算法结构简单、计算量适中且收敛速度快,弥补了一般变步长LMS自适应算法计算量小但收敛速度欠佳,以及仿射投影算法(APA)收敛速度快但计算量非常大的缺陷.该算法计算量与一般LMS算法相当,而收敛速度却与APA算法相当,其结构比APA及相应的改进算法要简单得多.我们不仅对所提算法的收敛性及性能进行了分析,而且将它用于多路回波消除中获得了成功,仿真结果表明,该算法与Sankaran(1997)所提NLMS-OCF算法及Benesty(1996)所提APA-MC算法比较,在收敛速度和收敛精度相当的情况下,其计算复杂度大大减少.从而新算法具备更好的实时性.