离散余弦变换的一种推广

离散余弦变换(DCT)在数字信号、图像处理、频谱分析、数据压缩和信息隐藏等领域有着广泛的应用.推广离散余弦变换,给出一个包含三个参数的统一表达式,并证明在许多情形新变换是正交变换.最后给出一种新型离散余弦变换,并证明它是正交变换.     

任意长度离散余弦变换的快速算法

§1.引言 离散余弦变换(DCT)有趋于统计最佳交换Kavhunven-Lave变换(KLT)的渐近性质,在通信和信号处理中应用广泛,并在许多方面比离散富里叶变换(DFT)更好。     

基于部分三角函数变换矩阵的块压缩感知测量方法

为了提高块压缩感知的测量效率和重构性能,根据离散余弦变换和离散正弦变换具有汇聚信号能量的特性,提出了基于重复块对角结构的部分离散余弦变换partial discrete cosine transform in repeated block diagonal structure,简称PDCT-RBDS和部分离散正弦变换partial discrete sine transform in repeated block diagonal structure简称PDST-RBDS的两种压缩感知测量方法.所采用的测量矩阵是一种低复杂度的结构化确定性矩阵, 满足受限等距性质.并得到一个与采样能量有关的受限等距常数和精确重构的测量数下限.通过与采用重复块对角结构的部分随机高斯矩阵和部分贝努利矩阵的图像压缩感知对比,结果表明PDCT-RBDS和PDST-RBDS重构的PSNR大约提高1---5dBSSIM提高约0.05, 所需的重构时间和测量矩阵的存储空间大大减少.该方法特别适合大规模图像压缩及实时视频数据处理场合.     

任意长度DCT—Ⅱ的MIMD并行算法

1 引 言 Ⅱ型离散余弦变换(DCT—Ⅱ)有超于统计最佳变换Karhunen—Loeve变换(KLT)的渐近性质,因而在通信和信号处理中得到了广泛应用,尤其是在图像处理中它是最有用的变换。设x(k)(k=0,1,…,N—1)为实数序例,其DCT—Ⅱ的定义为 X(n)=sum from k=0 to N-1 x(k)cos(π(2k+1)n)/2N,n=0,1,…,N-1。 (1)     

无界弦自由振动问题的算法

探讨了无界弦自由振动问题的两种算法：行波法和积分变换法，主要就积分变换法利用富里叶变换和matlab软件使得计算更简单，并给出了积分变换法的一般算法．     

用多项式变换计算多维离散W变换

1．引言多维离散W变换作为多维离散Hartley变换的推广［1－3］，是处理多维问题的一种工具．在计算机视觉、高清晰度电视（HDTV）以及可视电话等领域，经常要对运动图象进行分析和处理，通常称为多帧检测（Multi－WameDetection，简称MFD）［4－5］，这时三维离散w变换是一种可行的方法．由于不需要进行复数运算，比三维离散傅立叶交换（DFT）有优越性．而对运动的三维图象进行处理时，可采用四维离散w变换．对维数更高的多维信号进行处理时，可采用多维离散w变换．对三维以上的w变换，需要的运算量非常大，设计好的快速算法极为重要…     

含参变量富里叶级数的Laplace变换求和法

本文建立了含参变量富里叶级数的Laplace变换求和定理.利用Laplace变换表可以求得许多在力学上有重要应用的新的含参变量富里叶级数的和式.     

三维DFT的FPT算法

本导出了一种三堆离散富氏变换(DFT)的快速多项式变换(FPT)算法，并对该算法的计算量与通常所用算法(行列法)进行了比较，最后对算法的优劣作了总结．     

N=2^t点DFT的快速卷积算法

从所周知,循环卷积和离散富里叶变换(DFT)可以互相计算,只要得到其中一个的快速算法就可导出另一个的快速算法。循环卷积目前已有乘法量为O(N)的最佳算法(特别是当N较小时),为此关键是如何将DFT转化为循环卷积,当DFT的长度N=p(p为素数),Rader利用有限域GF(p)的乘法群是循环群就成功地将p点DFT转化为Q(p)(F(p)为户的Euler函数)点循环卷积;当N=p~e时,由于商环Z/(p~e)存在F(p~c)阶元素,人们也成功地将p~c点DFT转化为P(p~(c-1))一系列循环卷积,即一个y(p~c)点循环卷积,二个P(p~(c-1))点     

离散Ter变换的快速算法

本文研究了第 ( 2 ,0 )类离散 Walsh-Haar类变换即离散 Ter变换的快速算法 .     

Continuous and discrete Bessel wavelet transforms

Using the theory of Hankel convolution, continuous and discrete Bessel wavelet transforms are defined. Certain boundedness results and inversion formula for the continuous Bessel wavelet transform are obtained. Important properties of the discrete Bessel wavelet transform are given.     

Fast Wavelet Transform for Toeplitz Matrices and Property Analysis

Fast wavelet transform algorithms for Toeplitz matrices are proposed in this paper. Distinctive from the well known discrete trigonometric transforms, such as the discrete cosine transform （DCT） and the discrete Fourier transform （DFT） for Toeplitz matrices, the new algorithms are achieved by compactly supported wavelet that preserve the character of a Toeplitz matrix after transform, which is quite useful in many applications involving a Toeplitz matrix. Results of numerical experiments show that the proposed method has good compression performance similar to using wavelet in the digital image coding. Since the proposed algorithms turn a dense Toeplitz matrix into a band-limited form, the arithmetic operations required by the new algorithms are O（N） that are reduced greatly compared with O（N log N） by the classical trigonometric transforms.     

Difference operators,Green's matrix,sampling theory and applications in signal processing

This paper introduces sampling representations for discrete signals arising from self adjoint difference operators with mixed boundary conditions. The theory of linear operators on finite-dimensional inner product spaces is employed to study the second-order difference operators. We give necessary and sufficient conditions that make the operators self adjoint. The equivalence between the difference operator and a Hermitian Green's matrix is established. Sampling theorems are derived for discrete transforms associated with the difference operator. The results are exhibited via illustrative examples, involving sampling representations for the discrete Hartley transform. Families of discrete fractional Fourier-type transforms are introduced with an application to image encryption.     

A robust chaotic algorithm for digital image steganography

This paper proposes a new robust chaotic algorithm for digital image steganography based on a 3-dimensional chaotic cat map and lifted discrete wavelet transforms. The irregular outputs of the cat map are used to embed a secret message in a digital cover image. Discrete wavelet transforms are used to provide robustness. Sweldens’ lifting scheme is applied to ensure integer-to-integer transforms, thus improving the robustness of the algorithm. The suggested scheme is fast, efficient and flexible. Empirical results are presented to showcase the satisfactory performance of our proposed steganographic scheme in terms of its effectiveness (imperceptibility and security) and feasibility. Comparison with some existing transform domain steganographic schemes is also presented.     

Use of Divided Differences and B Splines for Constructing Fast Discrete Transforms of Wavelet Type on Nonuniform Grids

In this paper, we construct fast discrete transforms of wavelet type with an arbitrary number of zero moments for nonuniform grids. We obtain explicit formulas for the parameters defining the wavelet transform.__________Translated from Matematicheskie Zametki, vol. 77, no. 5, 2005, pp. 743–752.Original Russian Text Copyright ©2005 by I. V. Oseledets.     

In honor of Professor Dr. Wolfgang Haack on the occasion of his seventieth birthday on April 24, 1972

A discrete transform with a Bessel function kernel is defined, as a finite sum, over the zeros of the Bessel function. The approximate inverse of this transform is derived as another finite sum. This development is in parallel to that of the discrete Fourier transform (DFT) which lead to the fast Fourier transform (FFT) algorithm. The discrete Hankel transform with kernel Jo, the Bessel function of the first kind of order zero, will be used as an illustration for deriving the discrete Hankel transform, its inverse and a number of its basic properties. This includes the convolution product which is necessary for solving boundary problems. Other applications include evaluating Hankel transforms, Bessel series and replacing higher dimension Fourier transforms, with circular symmetry, by a single Hankel transform     

A hybrid Fourier transform

A Fourier transform akin to Sneddon's R-transform is introduced. It is shown that the Hilbert transform links the two in much the same way as it connects the classical Fourier sine and cosine transforms.     

Computation of the fractional Fourier transform

In this paper we make a critical comparison of some programs for the digital computation of the fractional Fourier transform that are freely available and we describe our own implementation that filters the best out of the existing ones. Two types of transforms are considered: first, the fast approximate fractional Fourier transform algorithm for which two algorithms are available. The method is described in [H.M. Ozaktas, M.A. Kutay, G. Bozda i, IEEE Trans. Signal Process. 44 (1996) 2141–2150]. There are two implementations: one is written by A.M. Kutay, the other is part of package written by J. O'Neill. Second, the discrete fractional Fourier transform algorithm described in the master thesis by Ç. Candan [Bilkent University, 1998] and an algorithm described by S.C. Pei, M.H. Yeh, and C.C. Tseng [IEEE Trans. Signal Process. 47 (1999) 1335–1348].     

Convolution theorem for fractional cosine‐sine transform and its application

Fractional cosine transform (FRCT) and fractional sine transform (FRST), which are closely related to the fractional Fourier transform (FRFT), are useful mathematical and optical tool for signal processing. Many properties for these transforms are well investigated, but the convolution theorems are still to be determined. In this paper, we derive convolution theorems for the fractional cosine transform (FRCT) and fractional sine transform (FRST) based on the four novel convolution operations. And then, a potential application for these two transforms on designing multiplicative filter is presented. Copyright © 2016 John Wiley & Sons, Ltd.